Stem seri$ (all stems)

310 papers:

SIGMOD-2015-AllardHMP #clustering #named #privacy

Chiaroscuro: Transparency and Privacy for Massive Personal Time-Series Clustering (TA, GH, FM, EP), pp. 779–794.

SIGMOD-2015-PaparrizosG #clustering #named #performance

k-Shape: Efficient and Accurate Clustering of Time Series (JP, LG), pp. 1855–1870.

SIGMOD-2015-SakuraiMF #mining

Mining and Forecasting of Big Time-series Data (YS, YM, CF), pp. 919–922.

SIGMOD-2015-ZhouT #named #predict

SMiLer: A Semi-Lazy Time Series Prediction System for Sensors (JZ, AKHT), pp. 1871–1886.

VLDB-2015-DingWDFZZ #clustering #named #performance #scalability

YADING: Fast Clustering of Large-Scale Time Series Data (RD, QW, YD, QF, HZ, DZ), pp. 473–484.

VLDB-2015-PelkonenFCHMTV #database #in memory #named #performance #scalability

Gorilla: A Fast, Scalable, In-Memory Time Series Database (TP, SF, PC, QH, JM, JT, KV), pp. 1816–1827.

VLDB-2015-ZoumpatianosIP #interactive #named

RINSE: Interactive Data Series Exploration with ADS+ (KZ, SI, TP), pp. 1912–1923.

SANER-2015-BaoLXWZ #interactive #reverse engineering

Reverse engineering time-series interaction data from screen-captured videos (LB, JL, ZX, XW, BZ), pp. 399–408.

LATA-2015-BaillyDR

Recognizable Series on Hypergraphs (RB, FD, GR), pp. 639–651.

ICEIS-v1-2015-Xylogiannopoulos #detection #roadmap

Discretization Method for the Detection of Local Extrema and Trends in Non-discrete Time Series (KFX, PK, RA), pp. 346–352.

ICEIS-v2-2015-SouzaVS #analysis #semantics

Semantically Enriching the Detrending Step of Time Series Analysis (LdS, MSMGV, MSS), pp. 475–481.

ICML-2015-AnavaHZ #online #predict

Online Time Series Prediction with Missing Data (OA, EH, AZ), pp. 2191–2199.

ICML-2015-BahadoriKFL #clustering #functional

Functional Subspace Clustering with Application to Time Series (MTB, DCK, YF, YL), pp. 228–237.

KDD-2015-BarajasA #approach #health #modelling

Dynamically Modeling Patient’s Health State from Electronic Medical Records: A Time Series Approach (KLCB, RA), pp. 69–78.

KDD-2015-CaiTFJH #higher-order #mining #named #performance

Facets: Fast Comprehensive Mining of Coevolving High-order Time Series (YC, HT, WF, PJ, QH), pp. 79–88.

KDD-2015-LaptevAF #automation #detection #framework #scalability

Generic and Scalable Framework for Automated Time-series Anomaly Detection (NL, SA, IF), pp. 1939–1947.

KDD-2015-Shokoohi-Yekta0

Discovery of Meaningful Rules in Time Series (MSY, YC, BJLC, BH, JZ, EJK), pp. 1085–1094.

KDD-2015-UlanovaYCJKZ #performance #physics #profiling

Efficient Long-Term Degradation Profiling in Time Series for Complex Physical Systems (LU, TY, HC, GJ, EJK, KZ), pp. 2167–2176.

KDD-2015-ZoumpatianosLPG #query

Query Workloads for Data Series Indexes (KZ, YL, TP, JG), pp. 1603–1612.

MLDM-2015-AkbariniaM #probability #streaming

Aggregation-Aware Compression of Probabilistic Streaming Time Series (RA, FM), pp. 232–247.

SEKE-2015-TunnellA #fault #modelling #predict #release planning #using

Using Time Series Models for Defect Prediction in Software Release Planning (JT, JA), pp. 451–454.

CASE-2014-YamazakiSYI #3d #modelling

3D shape modeling of movable parts of furniture based on time-series surface correspondence (KY, KS, TY, MI), pp. 249–254.

SIGMOD-2014-ZoumpatianosIP #big data #interactive

Indexing for interactive exploration of big data series (KZ, SI, TP), pp. 1555–1566.

VLDB-2014-JugelJM #named #visualisation

M4: A Visualization-Oriented Time Series Data Aggregation (UJ, ZJ, GH, VM), pp. 797–808.

VLDB-2015-BegumK14 #bound

Rare Time Series Motif Discovery from Unbounded Streams (NB, EJK), pp. 149–160.

VLDB-2015-DallachiesaPI14 #nearest neighbour #nondeterminism

Top-k Nearest Neighbor Search In Uncertain Data Series (MD, TP, IFI), pp. 13–24.

CHI-2014-AlbersCG #evaluation #visualisation

Task-driven evaluation of aggregation in time series visualization (DA, MC, MG), pp. 551–560.

CHI-2014-SchirraSB #twitter

Together alone: motivations for live-tweeting a television series (SS, HS, FB), pp. 2441–2450.

HIMI-AS-2014-XingGLK #clustering

Decision Support Based on Time-Series Analytics: A Cluster Methodology (WX, RG, NL, TRK), pp. 217–225.

HIMI-DE-2014-KobayashiS #corpus #topic

Finding Division Points for Time-Series Corpus Based on Topic Changes (HK, RS), pp. 364–372.

ICEIS-v1-2014-AmaralCRGTS #approach #data mining #framework #image #mining

The SITSMining Framework — A Data Mining Approach for Satellite Image Time Series (BFA, DYTC, LASR, RRdVG, AJMT, EPMdS), pp. 225–232.

ICEIS-v1-2014-ChinoGRTT #named #scalability

TrieMotif — A New and Efficient Method to Mine Frequent K-Motifs from Large Time Series (DYTC, RRdVG, LASR, CTJ, AJMT), pp. 60–69.

ICEIS-v2-2014-SouzaVS #ontology

Domain Ontology for Time Series Provenance (LdS, MSMGV, MSS), pp. 217–224.

CIKM-2014-XuHCWHBA #framework #performance

A Demonstration of SearchonTS: An Efficient Pattern Search Framework for Time Series Data (XX, SH, YC, CW, IH, KB, MA), pp. 2015–2017.

ICML-c1-2014-KhaleghiR #consistency #estimation

Asymptotically consistent estimation of the number of change points in highly dependent time series (AK, DR), pp. 539–547.

ICML-c2-2014-Chapados #effectiveness #modelling

Effective Bayesian Modeling of Groups of Related Count Time Series (NC), pp. 1395–1403.

ICML-c2-2014-JohnsonW #modelling #probability

Stochastic Variational Inference for Bayesian Time Series Models (MJ, ASW), pp. 1854–1862.

ICML-c2-2014-WangY #crowdsourcing

Ensemble-Based Tracking: Aggregating Crowdsourced Structured Time Series Data (NW, DYY), pp. 1107–1115.

ICPR-2014-BauckhageM #analysis #clustering #kernel #web

Kernel Archetypal Analysis for Clustering Web Search Frequency Time Series (CB, KM), pp. 1544–1549.

ICPR-2014-ChevallierCA #estimation #image #metric #orthogonal #using

Computing Histogram of Tensor Images Using Orthogonal Series Density Estimation and Riemannian Metrics (EC, AC, JA), pp. 900–905.

ICPR-2014-ContiFAAMCT #detection #distance #evaluation

Evaluation of Time Series Distance Functions in the Task of Detecting Remote Phenology Patterns (JCC, FAF, JA, BA, LPCM, LC, RdST), pp. 3126–3131.

ICPR-2014-DamoulasHBGA #kernel #string

String Kernels for Complex Time-Series: Counting Targets from Sensed Movement (TD, JH, RB, CPG, AA), pp. 4429–4434.

ICPR-2014-SousaSB #case study #classification #set

Time Series Transductive Classification on Imbalanced Data Sets: An Experimental Study (CARdS, VMAdS, GEAPAB), pp. 3780–3785.

ICPR-2014-SouzaSB #classification

Extracting Texture Features for Time Series Classification (VMAdS, DFS, GEAPAB), pp. 1425–1430.

KDD-2014-ChengB0 #approach #dependence #effectiveness #named

FBLG: a simple and effective approach for temporal dependence discovery from time series data (DC, MTB, YL), pp. 382–391.

KDD-2014-ChiaS #mining #predict #scalability

Scalable noise mining in long-term electrocardiographic time-series to predict death following heart attacks (CCC, ZS), pp. 125–134.

KDD-2014-GrabockaSWS #learning

Learning time-series shapelets (JG, NS, MW, LST), pp. 392–401.

KDD-2014-LuoLLFDZW #correlation

Correlating events with time series for incident diagnosis (CL, JGL, QL, QF, RD, DZ, ZW), pp. 1583–1592.

MLDM-2014-Schafer #classification #preprocessor #towards

Towards Time Series Classification without Human Preprocessing (PS), pp. 228–242.

MLDM-2014-YuST #detection #modelling #realtime

Semi-supervised Time Series Modeling for Real-Time Flux Domain Detection on Passive DNS Traffic (BY, LS, MT), pp. 258–271.

SEKE-2014-Otunba0 #approximate #detection #named

APT: Approximate Period Detection in Time Series (RO, JL), pp. 490–494.

SEKE-2014-XuS #automation #effectiveness #petri net #testing

Effectiveness of Automated Function Testing with Petri Nets: A Series of Controlled Experiments (DX, NS), pp. 211–216.

REFSQ-2014-AbeleinP #communication #developer #scalability

State of Practice of User-Developer Communication in Large-Scale IT Projects — Results of an Expert Interview Series (UA, BP), pp. 95–111.

SAC-2014-SpiegelJA #classification #distance #performance

Fast time series classification under lucky time warping distance (SS, BJJ, SA), pp. 71–78.

CASE-2013-ZhouKZS #analysis

Causal analysis for non-stationary time series in sensor-rich smart buildings (YZ, ZK, LZ, CJS), pp. 593–598.

DATE-2013-StergiouJ #dataset #optimisation

Optimizing BDDs for time-series dataset manipulation (SS, JJ), pp. 1018–1021.

ICDAR-2013-GriechischML #analysis #online

Online Signature Analysis Based on Accelerometric and Gyroscopic Pens and Legendre Series (EG, MIM, ML), pp. 374–378.

VLDB-2013-0002GJ #correlation #markov #modelling #using

Travel Cost Inference from Sparse, Spatio-Temporally Correlated Time Series Using Markov Models (BY, CG, CSJ), pp. 769–780.

VLDB-2013-WangWPWH #adaptation #segmentation

A Data-adaptive and Dynamic Segmentation Index for Whole Matching on Time Series (YW, PW, JP, WW, SH), pp. 793–804.

VLDB-2014-EravciF13 #feedback

Diversity based Relevance Feedback for Time Series Search (BE, HF), pp. 109–120.

CHI-2013-FuchsFMBI #design #evaluation #multi

Evaluation of alternative glyph designs for time series data in a small multiple setting (JF, FF, FM, EB, PI), pp. 3237–3246.

CHI-2013-PerinVF #graph #interactive #multi #visualisation

Interactive horizon graphs: improving the compact visualization of multiple time series (CP, FV, JDF), pp. 3217–3226.

ICEIS-v1-2013-AndradeRYS #data-driven #database #novel #similarity

A Novel Method for Similarity Search over Meteorological Time Series Data based on the Coulomb’s Law (CGdA, MXR, CAY, MTPS), pp. 209–216.

CIKM-2013-KimCHZRD #feedback #mining #modelling #topic

Mining causal topics in text data: iterative topic modeling with time series feedback (HDK, MC, MH, CZ, TAR, DD), pp. 885–890.

ICML-c1-2013-WulsinFL #correlation #markov #parsing #process #using

Parsing epileptic events using a Markov switching process model for correlated time series (DW, EBF, BL), pp. 356–364.

ICML-c2-2013-GaneshapillaiGL #learning

Learning Connections in Financial Time Series (GG, JVG, AL), pp. 109–117.

ICML-c2-2013-HanL #estimation #matrix

Transition Matrix Estimation in High Dimensional Time Series (FH, HL), pp. 172–180.

ICML-c3-2013-WuHG #modelling #multi

Dynamic Covariance Models for Multivariate Financial Time Series (YW, JMHL, ZG), pp. 558–566.

KDD-2013-ChenHKB #learning #named

DTW-D: time series semi-supervised learning from a single example (YC, BH, EJK, GEAPAB), pp. 383–391.

KDD-2013-ChenTTY #analysis #kernel #modelling #performance

Model-based kernel for efficient time series analysis (HC, FT, PT, XY), pp. 392–400.

KDD-2013-HaoCZ0RK #learning #towards

Towards never-ending learning from time series streams (YH, YC, JZ, BH, TR, EJK), pp. 874–882.

KDD-2013-RistanoskiLB

A time-dependent enhanced support vector machine for time series regression (GR, WL, JB), pp. 946–954.

MLDM-2013-VavreckaL #classification #feature model

EEG Feature Selection Based on Time Series Classification (MV, LL), pp. 520–527.

RecSys-2013-SchelterBSAM #distributed #matrix #pipes and filters #using

Distributed matrix factorization with mapreduce using a series of broadcast-joins (SS, CB, MS, AA, VM), pp. 281–284.

SIGIR-2013-Soboroff #evaluation #interactive #student #tutorial

Building test collections: an interactive tutorial for students and others without their own evaluation conference series (IS), p. 1132.

SPLC-2013-TsuchiyaKWKFY #requirements #source code #traceability

Recovering traceability links between requirements and source code in the same series of software products (RT, TK, HW, MK, YF, KY), pp. 121–130.

ASE-2012-AminGC #approach #automation #linear #modelling

An automated approach to forecasting QoS attributes based on linear and non-linear time series modeling (AA, LG, AC), pp. 130–139.

CASE-2012-ChenZD #fourier #process

Mitigation of chatter instability in milling processes by active fourier series compensation (ZC, HTZ, HD), pp. 167–171.

HT-2012-NakajimaZIN #analysis #detection #scalability

Early detection of buzzwords based on large-scale time-series analysis of blog entries (SN, JZ, YI, RYN), pp. 275–284.

VLDB-2012-DallachiesaNMP #nondeterminism #similarity

Uncertain Time-Series Similarity: Return to the Basics (MD, BN, KM, TP), pp. 1662–1673.

STOC-2012-ChakrabartiFW #multi #network #problem

When the cut condition is enough: a complete characterization for multiflow problems in series-parallel networks (AC, LF, CW), pp. 19–26.

CIAA-2012-LiuSGF #automaton #named #regular expression

SDFA: Series DFA for Memory-Efficient Regular Expression Matching (TL, YS, LG, BF), pp. 337–344.

CHI-2012-CorrellAFG

Comparing averages in time series data (MC, DA, SF, MG), pp. 1095–1104.

CIKM-2012-CandanRSW #named #scalability #set #visualisation

STFMap: query- and feature-driven visualization of large time series data sets (KSC, RR, MLS, XW), pp. 2743–2745.

CIKM-2012-KimZRDHCL #mining #named #topic

InCaToMi: integrative causal topic miner between textual and non-textual time series data (HDK, CZ, TAR, DD, MH, MC, CCL), pp. 2689–2691.

CIKM-2012-LiangZ #classification #performance

An efficient and simple under-sampling technique for imbalanced time series classification (GL, CZ), pp. 2339–2342.

CIKM-2012-OrangS #approach #correlation #nondeterminism #probability #query

A probabilistic approach to correlation queries in uncertain time series data (MO, NS), pp. 2229–2233.

ICML-2012-JalaliS #dependence #graph #learning

Learning the Dependence Graph of Time Series with Latent Factors (AJ, SS), p. 83.

ICML-2012-LiuL #modelling #multi #named

Sparse-GEV: Sparse Latent Space Model for Multivariate Extreme Value Time Serie Modeling (YL, MTB, HL), p. 156.

ICPR-2012-HidoM #feature model #predict

Temporal feature selection for time-series prediction (SH, TM), pp. 3557–3560.

ICPR-2012-LiuXFLMK #classification #modelling #multi #statistics

Statistical modeling and signal selection in multivariate time series pattern classification (RL, SX, CF, YwL, YLM, DSK), pp. 2853–2856.

ICPR-2012-SuematsuH #process

Time series alignment with Gaussian processes (NS, AH), pp. 2355–2358.

KDD-2012-BatalFHMH #detection #mining #multi

Mining recent temporal patterns for event detection in multivariate time series data (IB, DF, JH, FM, MH), pp. 280–288.

KDD-2012-LinesDHB #classification

A shapelet transform for time series classification (JL, LMD, JH, AB), pp. 289–297.

KDD-2012-RakthanmanonCMBWZZK #mining #sequence

Searching and mining trillions of time series subsequences under dynamic time warping (TR, BJLC, AM, GEAPAB, MBW, QZ, JZ, EJK), pp. 262–270.

KDIR-2012-SpiegelA #analysis #distance #invariant

An Order-invariant Time Series Distance Measure — Position on Recent Developments in Time Series Analysis (SS, SA), pp. 264–268.

SAC-2012-LiLXZR #named

TL-Tree: flash-optimized storage for time-series sensing data on sensor platforms (HL, DL, LX, GZ, KR), pp. 1565–1572.

SAC-2012-SchluterC #correlation #detection #markov #modelling #predict #using

Hidden markov model-based time series prediction using motifs for detecting inter-time-serial correlations (TS, SC), pp. 158–164.

SIGMOD-2011-WangWW #semantics

Finding semantics in time series (PW, HW, WW), pp. 385–396.

CHI-2011-ZhaoCB #multi #named #navigation #using #visual notation

KronoMiner: using multi-foci navigation for the visual exploration of time-series data (JZ, FC, RB), pp. 1737–1746.

ICEIS-J-2011-NganBL11a #framework #learning #monitoring #multi #query

An Event-Based Service Framework for Learning, Querying and Monitoring Multivariate Time Series (CKN, AB, JL), pp. 208–223.

ICEIS-v1-2011-NiknafsSRR #analysis #comparative #predict

Comparative Analysis of Three Techniques for Predictions in Time Series Having Repetitive Patterns (AN, BS, MMR, GR), pp. 177–182.

ICEIS-v2-2011-NganBL #framework #learning #monitoring #multi #query

A Service Framework for Learning, Querying and Monitoring Multivariate Time Series (CKN, AB, JL), pp. 92–101.

ICEIS-v2-2011-TarsauliyaTS #network #search-based #using

Financial Time Series Forecast using Simulated Annealing and Threshold Acceptance Genetic BPA Neural Network (AT, RT, AS), pp. 172–177.

ICML-2011-LiP #clustering #exclamation

Time Series Clustering: Complex is Simpler! (LL, BAP), pp. 185–192.

KDD-2011-KashyapK #scalability

Scalable kNN search on vertically stored time series (SK, PK), pp. 1334–1342.

KDD-2011-MueenKY #classification #named

Logical-shapelets: an expressive primitive for time series classification (AM, EJK, NEY), pp. 1154–1162.

KDD-2011-TorgoO #2d #predict

2D-interval predictions for time series (LT, OO), pp. 787–794.

KDIR-2011-WongLZYFXKC #case study #segmentation

Time Series Segmentation as a Discovery Tool — A Case Study of the US and Japanese Financial Markets (JCW, GHTL, YZ, WSY, RPF, DYX, JLK, SAC), pp. 52–63.

MLDM-2011-ArmstrongD #database #scalability

Unsupervised Discovery of Motifs under Amplitude Scaling and Shifting in Time Series Databases (TA, ED), pp. 539–552.

SIGIR-2011-Shokouhi #analysis #detection #query

Detecting seasonal queries by time-series analysis (MS), pp. 1171–1172.

SIGMOD-2010-MueenNL #approximate #correlation #performance

Fast approximate correlation for massive time-series data (AM, SN, JL), pp. 171–182.

SIGMOD-2010-RastogiN #distributed #encryption

Differentially private aggregation of distributed time-series with transformation and encryption (VR, SN), pp. 735–746.

VLDB-2010-LiPF #linear

Parsimonious Linear Fingerprinting for Time Series (LL, BAP, CF), pp. 385–396.

ICSM-2010-CanforaCCP #detection #empirical #logic #multi #using

Using multivariate time series and association rules to detect logical change coupling: An empirical study (GC, MC, LC, MDP), pp. 1–10.

CIKM-2010-ShangCSCH #towards

(k, P)-anonymity: towards pattern-preserving anonymity of time-series data (XS, KC, LS, GC, TH), pp. 1333–1336.

CIKM-2010-ZhaoAY #composition #nondeterminism #on the #set

On wavelet decomposition of uncertain time series data sets (YZ, CCA, PSY), pp. 129–138.

ICML-2010-ChenW #modelling

Dynamical Products of Experts for Modeling Financial Time Series (YC, MW), pp. 207–214.

ICML-2010-LiuNLL #analysis #graph #learning #relational

Learning Temporal Causal Graphs for Relational Time-Series Analysis (YL, ANM, ACL, YL), pp. 687–694.

ICPR-2010-ChiuHW #clustering

AP-Based Consensus Clustering for Gene Expression Time Series (TYC, TCH, JSW), pp. 2512–2515.

ICPR-2010-LewandowskiRMN #reduction

Temporal Extension of Laplacian Eigenmaps for Unsupervised Dimensionality Reduction of Time Series (ML, JMdR, DM, JCN), pp. 161–164.

ICPR-2010-SeyedhosseiniPT #classification #image #network #parsing

Image Parsing with a Three-State Series Neural Network Classifier (MS, ARCP, TT), pp. 4508–4511.

ICPR-2010-ZhangZZZ #classification #kernel #metric #using

Time Series Classification Using Support Vector Machine with Gaussian Elastic Metric Kernel (DZ, WZ, DZ, HZ), pp. 29–32.

KDD-2010-MueenK #maintenance #online

Online discovery and maintenance of time series motifs (AM, EJK), pp. 1089–1098.

KDD-2010-SarangiM #named #nondeterminism #similarity

DUST: a generalized notion of similarity between uncertain time series (SRS, KM), pp. 383–392.

SAC-2010-AraujoOS #hybrid #quantum

Hybrid evolutionary quantum inspired method to adjust time phase distortions in financial time series (RdAA, ALIdO, SCBS), pp. 1153–1154.

SAC-2010-LuoTLTDW #design #enterprise #evaluation #process #visualisation

Visualizing time-series data in processlines: design and evaluation of a process enterprise application (XL, FT, WL, DT, GD, HW), pp. 1165–1172.

SAC-2010-MarascuML #approximate #performance #set #streaming

A fast approximation strategy for summarizing a set of streaming time series (AM, FM, YL), pp. 1617–1621.

SAC-2010-RomaniAZCTT #algorithm #mining #named

CLEARMiner: a new algorithm for mining association patterns on heterogeneous time series from climate data (LASR, AMHdÁ, JZJ, RC, CTJ, AJMT), pp. 900–905.

ICDAR-2009-GolubitskyW #multi #online #orthogonal #recognition

Online Recognition of Multi-Stroke Symbols with Orthogonal Series (OG, SMW), pp. 1265–1269.

VLDB-2009-AssentWKKS #database #performance #similarity

Anticipatory DTW for Efficient Similarity Search in Time Series Databases (IA, MW, RK, HK, TS), pp. 826–837.

VLDB-2009-ReevesLNZ #multi

Managing Massive Time Series Streams with MultiScale Compressed Trickles (GR, JL, SN, FZ), pp. 97–108.

DLT-2009-Kirsten #commutative

The Support of a Recognizable Series over a Zero-Sum Free, Commutative Semiring Is Recognizable (DK), pp. 326–333.

LATA-2009-BaillyD #convergence

Absolute Convergence of Rational Series Is Semi-decidable (RB, FD), pp. 117–128.

LATA-2009-MatsubaraKBS #string

A Series of Run-Rich Strings (WM, KK, HB, AS), pp. 578–587.

CHI-2009-HeerKA #visual notation #visualisation

Sizing the horizon: the effects of chart size and layering on the graphical perception of time series visualizations (JH, NK, MA), pp. 1303–1312.

ICML-2009-PetersJGS #detection

Detecting the direction of causal time series (JP, DJ, AG, BS), pp. 801–808.

KDD-2009-ShibuyaHK #modelling #multi #quantifier

Causality quantification and its applications: structuring and modeling of multivariate time series (TS, TH, YK), pp. 787–796.

KDD-2009-YeK #data mining #mining

Time series shapelets: a new primitive for data mining (LY, EJK), pp. 947–956.

MLDM-2009-NikovskiR #modelling #predict

Memory-Based Modeling of Seasonality for Prediction of Climatic Time Series (DN, GR), pp. 734–748.

MLDM-2009-ZhuFF #classification #privacy

Preserving Privacy in Time Series Data Classification by Discretization (YZ, YF, HF), pp. 53–67.

SAC-2009-FlorezL #video

Discovery of time series in video data through distribution of spatiotemporal gradients (OUF, SL), pp. 1816–1820.

DAC-2008-PangR #fixpoint #optimisation

Optimizing imprecise fixed-point arithmetic circuits specified by Taylor Series through arithmetic transform (YP, KR), pp. 397–402.

SIGMOD-2008-AthitsosPPKG #approximate #sequence

Approximate embedding-based subsequence matching of time series (VA, PP, MP, GK, DG), pp. 365–378.

VLDB-2008-DingTSWK #comparison #distance #metric #mining #query

Querying and mining of time series data: experimental comparison of representations and distance measures (HD, GT, PS, XW, EJK), pp. 1542–1552.

MSR-2008-SiyCS #challenge #developer #segmentation #using

Summarizing developer work history using time series segmentation: challenge report (HPS, PC, MS), pp. 137–140.

CIAA-2008-Maletti

Tree-Series-to-Tree-Series Transformations (AM), pp. 132–140.

ICALP-B-2008-Mathissen #algebra #logic #word

Weighted Logics for Nested Words and Algebraic Formal Power Series (CM), pp. 221–232.

CHI-2008-McLachlanMKN #interactive #named #visual notation

LiveRAC: interactive visual exploration of system management time-series data (PM, TM, EK, SCN), pp. 1483–1492.

ICEIS-AIDSS-2008-NguyenG #approach #evolution #mining #multi

Rule Evolution Approach for Mining Multivariate Time Series Data (VAN, VG), pp. 19–26.

CIKM-2008-NguyenS #analysis #correlation #dataset #performance

Fast correlation analysis on time series datasets (PN, NS), pp. 787–796.

ECIR-2008-EuachongprasitR #multi #normalisation #performance #retrieval #scalability

Efficient Multimedia Time Series Data Retrieval Under Uniform Scaling and Normalisation (WE, CAR), pp. 506–513.

ICML-2008-LuLHE #framework #kernel

A reproducing kernel Hilbert space framework for pairwise time series distances (ZL, TKL, YH, DE), pp. 624–631.

ICPR-2008-HautamakiNF #approximate #clustering #prototype

Time-series clustering by approximate prototypes (VH, PN, PF), pp. 1–4.

ICPR-2008-KazuiMMF #detection #matrix #using

Incoherent motion detection using a time-series Gram matrix feature (MK, MM, SM, HF), pp. 1–5.

KDD-2008-ChengT #learning

Semi-supervised learning with data calibration for long-term time series forecasting (HC, PNT), pp. 133–141.

KDD-2008-ShiehK #mining #named

iSAX: indexing and mining terabyte sized time series (JS, EJK), pp. 623–631.

ICSE-2008-RiccaPTTCV #evolution

Are fit tables really talking?: a series of experiments to understand whether fit tables are useful during evolution tasks (FR, MDP, MT, PT, MC, CAV), pp. 361–370.

SIGMOD-2007-MorseP #performance #similarity

An efficient and accurate method for evaluating time series similarity (MDM, JMP), pp. 569–580.

VLDB-2007-HanLMJ #database #sequence

Ranked Subsequence Matching in Time-Series Databases (WSH, JL, YSM, HJ), pp. 423–434.

VLDB-2007-LiH #approximate #mining #multi

Mining Approximate Top-K Subspace Anomalies in Multi-Dimensional Time-Series Data (XL, JH), pp. 447–458.

VLDB-2007-PapadimitriouLKY #privacy

Time Series Compressibility and Privacy (SP, FL, GK, PSY), pp. 459–470.

ICSM-2007-SiyCRS #developer #segmentation #version control

Discovering Dynamic Developer Relationships from Software Version Histories by Time Series Segmentation (HPS, PC, DJR, MS), pp. 415–424.

MSR-2007-HerraizGR07a #analysis #eclipse #using

Forecasting the Number of Changes in Eclipse Using Time Series Analysis (IH, JMGB, GR), p. 32.

WCRE-2007-RatzingerGP #assessment #evolution #quality

Quality Assessment Based on Attribute Series of Software Evolution (JR, HG, MP), pp. 80–89.

STOC-2007-BrinkmanKL #graph #random #reduction

Vertex cuts, random walks, and dimension reduction in series-parallel graphs (BB, AK, JRL), pp. 621–630.

LATA-2007-Martugin #automaton

A series of slowly synchronizable automata with a zero state over a small alphabet (PVM), pp. 391–402.

CIKM-2007-YangQZGL #analysis #graph #using #web

Link analysis using time series of web graphs (LY, LQ, YPZ, BG, TYL), pp. 1011–1014.

CIKM-2007-ZhangYGY #adaptation #analysis #correlation #representation

Boolean representation based data-adaptive correlation analysis over time series streams (TZ, DY, YG, GY), pp. 203–212.

ICML-2007-XuanM #dependence #modelling #multi

Modeling changing dependency structure in multivariate time series (XX, KPM), pp. 1055–1062.

KDD-2007-YankovKMCZ #detection #scalability

Detecting time series motifs under uniform scaling (DY, EJK, JM, BYcC, VBZ), pp. 844–853.

ICSE-2007-CarverKSP #case study #development

Software Development Environments for Scientific and Engineering Software: A Series of Case Studies (JCC, RPK, SES, DEP), pp. 550–559.

SIGMOD-2006-PapadimitriouY #multi

Optimal multi-scale patterns in time series streams (SP, PSY), pp. 647–658.

VLDB-2006-Keogh #database #mining #scalability

A Decade of Progress in Indexing and Mining Large Time Series Databases (EJK), p. 1268.

DLT-2006-Maletti #revisited

Hierarchies of Tree Series Transformations Revisited (AM), pp. 215–225.

CIKM-2006-GoldinMN #algorithm #clustering #distance #sequence

In search of meaning for time series subsequence clustering: matching algorithms based on a new distance measure (DQG, RM, GN), pp. 347–356.

CIKM-2006-GrecoRT #effectiveness #performance #similarity

Effective and efficient similarity search in time series (SG, MR, AT), pp. 808–809.

CIKM-2006-LiuJK #clustering #query

Measuring the meaning in time series clustering of text search queries (BL, RJ, KLK), pp. 836–837.

ICML-2006-XiKSWR #classification #performance #reduction #using

Fast time series classification using numerosity reduction (XX, EJK, CRS, LW, CAR), pp. 1033–1040.

ICPR-v3-2006-HuRH #approach #clustering #robust

An Interweaved HMM/DTW Approach to Robust Time Series Clustering (JH, BKR, LH), pp. 145–148.

ICPR-v4-2006-BrandtZ #robust

Robust Alignment of Transmission Electron Microscope Tilt Series (SSB, UZ), pp. 683–686.

KDD-2006-Morchen #algorithm #mining

Algorithms for time series knowledge mining (FM), pp. 668–673.

KDD-2006-WeiK #classification

Semi-supervised time series classification (LW, EJK), pp. 748–753.

KDD-2006-ZhangCFM #detection #recommendation

Attack detection in time series for recommender systems (SZ, AC, JF, FM), pp. 809–814.

ICSE-2006-LeeKC #development

A series of development methodologies for a variety of systems in Korea (JL, JSK, JHC), pp. 612–615.

DATE-2005-MartensG #integration #orthogonal #polynomial #simulation #using

Time-Domain Simulation of Sampled Weakly Nonlinear Systems Using Analytical Integration and Orthogonal Polynomial Series (EM, GGEG), pp. 120–125.

HT-2005-ToyodaK #evolution #graph #visualisation #web

A system for visualizing and analyzing the evolution of the web with a time series of graphs (MT, MK), pp. 151–160.

SIGMOD-2005-WuSSJSK #sequence

Subsequence Matching on Structured Time Series Data (HW, BS, GCS, SBJ, HS, DRK), pp. 682–693.

VLDB-2005-FuKLR #query #scalability

Scaling and Time Warping in Time Series Querying (AWCF, EJK, LYHL, C(R), pp. 649–660.

VLDB-2005-PapadimitriouSF #multi #streaming

Streaming Pattern Discovery in Multiple Time-Series (SP, JS, CF), pp. 697–708.

DLT-J-2004-Maletti05 #automaton #transducer

Relating tree series transducers and weighted tree automata (AM), pp. 723–741.

DLT-2005-Maletti #power of #transducer

The Power of Tree Series Transducers of Type I and II (AM), pp. 338–349.

ICEIS-v2-2005-CuellarDJ #network #predict #problem #programming

An Application of Non-Linear Programming to Train Recurrent Neural Networks in Time Series Prediction Problems (MPC, MD, MdCPJ), pp. 35–42.

ICEIS-v2-2005-NilssonFX #classification #using

Clinical Decision Support by Time Series Classification Using Wavelets (MN, PF, NX), pp. 169–175.

CIKM-2005-FuCTLN #incremental #visualisation

Incremental stock time series data delivery and visualization (TCF, FLC, PyT, RWPL, CmN), pp. 279–280.

CIKM-2005-LuoJH #estimation

Applying cosine series to join size estimation (CL, ZJ, WCH), pp. 227–228.

ICML-2005-SinghPGBB #analysis #learning

Active learning for sampling in time-series experiments with application to gene expression analysis (RS, NP, DKG, BB, ZBJ), pp. 832–839.

KDD-2005-ColeSZ #correlation #performance

Fast window correlations over uncooperative time series (RC, DS, XZ), pp. 743–749.

KDD-2005-MorchenU #information management #optimisation

Optimizing time series discretization for knowledge discovery (FM, AU), pp. 660–665.

MLDM-2005-BunkeDIK #analysis #graph #learning #predict

Analysis of Time Series of Graphs: Prediction of Node Presence by Means of Decision Tree Learning (HB, PJD, CI, MK), pp. 366–375.

MLDM-2005-HayashiMS #classification

Embedding Time Series Data for Classification (AH, YM, NS), pp. 356–365.

SAC-2005-FalcoTCP #approach #induction #programming #search-based

Inductive inference of chaotic series by Genetic Programming: a Solomonoff-based approach (IDF, ET, ADC, AP), pp. 957–958.

SAC-2005-GaoWW #evaluation #quality #streaming

Quality-driven evaluation of trigger conditions on streaming time series (LG, MW, XSW), pp. 563–567.

SAC-2005-KimJ #performance #sequence

Performance bottleneck in time-series subsequence matching (SWK, BSJ), pp. 469–473.

SAC-2005-KimKS #database #optimisation #sequence

Optimization of subsequence matching under time warping in time-series databases (MSK, SWK, MS), pp. 581–586.

SIGMOD-2004-LernerSWZZ #algorithm #biology #music #performance #physics

Fast Algorithms for Time Series with applications to Finance, Physics, Music, Biology, and other Suspects (AL, DS, ZW, XZ, YZ), pp. 965–968.

VLDB-2004-LinKLLN #database #mining #monitoring #named #visual notation

VizTree: a Tool for Visually Mining and Monitoring Massive Time Series Databases (JL, EJK, SL, JPL, DMN), pp. 1269–1272.

CIAA-2004-Borchardt #transducer

Code Selection by Tree Series Transducers (BB), pp. 57–67.

DLT-2004-ChoffrutGL #on the

On the Maximum Coefficients of Rational Formal Series in Commuting Variables (CC, MG, VL), pp. 114–126.

DLT-2004-Maletti #automaton #transducer

Relating Tree Series Transducers and Weighted Tree Automata (AM), pp. 321–333.

ICEIS-v2-2004-CamargoFPS #network #tool support

Neural Network and Time Series as Tools for Sales Forecasting (MC, WPF, MP, AS), pp. 476–478.

ICEIS-v2-2004-KooptiwootS #mining #set #using

Mining the Relationships in the Form of the Predisposing Factors and Coincident Factors Among Numerical Dynamic Attributes in Time Series Data Set by Using the Combination of Some Existing Techniques (SK, MAS), pp. 327–334.

ICEIS-v2-2004-KooptiwootS04a #idea #mining #set #using

Mining the Relationships in the Form of Predisposing Factor and Coincident Factor in Time Series Data Set by Using the Combination of some Existing Ideas with a new Idea from the Fact in the Chemical Reaction (SK, MAS), pp. 531–534.

ICEIS-v2-2004-UdechukwuBA #framework #mining #performance

An Efficient Framework for Iterative Time-Series Trend Mining (AU, KB, RA), pp. 130–137.

CIKM-2004-MegalooikonomouLW #analysis #database #performance #reduction #similarity

A dimensionality reduction technique for efficient similarity analysis of time series databases (VM, GL, QW), pp. 160–161.

ICPR-v3-2004-JiaQD #detection #markov #modelling #online

An Advanced Segmental Semi-Markov Model Based Online Series Pattern Detection (SJ, YQ, GD), pp. 634–637.

ICPR-v4-2004-LaiY #algorithm #fault #network #predict

Successive-Least-Squares Error Algorithm on Minimum Description Length Neural Networks for Time Series Prediction (YNL, SYY), pp. 609–612.

KDD-2004-AiroldiF #network

Recovering latent time-series from their observed sums: network tomography with particle filters (EA, CF), pp. 30–39.

KDD-2004-BagnallJ #clustering #modelling

Clustering time series from ARMA models with clipped data (AJB, GJJ), pp. 49–58.

KDD-2004-LinKLLN #mining #monitoring #visual notation

Visually mining and monitoring massive time series (JL, EJK, SL, JPL, DMN), pp. 460–469.

DATE-2003-YevtushenkoVBPS #equation

Equisolvability of Series vs. Controller’s Topology in Synchronous Language Equations (NY, TV, RKB, AP, ALSV), pp. 11154–11155.

HT-2003-ToyodaK #community #evolution #web

Extracting evolution of web communities from a series of web archives (MT, MK), pp. 28–37.

DLT-2003-Borchardt #theorem

The Myhill-Nerode Theorem for Recognizable Tree Series (BB), pp. 146–158.

DLT-2003-BouillardM #generative

Generating Series of the Trace Group (AB, JM), pp. 159–170.

ICALP-2003-DrosteK

Skew and Infinitary Formal Power Series (MD, DK), pp. 426–438.

ICML-2003-LangleyGBS #induction #modelling #process #robust

Robust Induction of Process Models from Time-Series Data (PL, DG, SDB, KS), pp. 432–439.

ICML-2003-YamadaSYT #data-driven #database #induction #standard

Decision-tree Induction from Time-series Data Based on a Standard-example Split Test (YY, ES, HY, KT), pp. 840–847.

KDD-2003-ChiuKL #probability

Probabilistic discovery of time series motifs (BYcC, EJK, SL), pp. 493–498.

KDD-2003-JiangPZ #interactive

Interactive exploration of coherent patterns in time-series gene expression data (DJ, JP, AZ), pp. 565–570.

KDD-2003-SripadaRHY #generative #summary #using

Generating English summaries of time series data using the Gricean maxims (SS, ER, JH, JY), pp. 187–196.

KDD-2003-VlachosHGK #distance #metric #multi

Indexing multi-dimensional time-series with support for multiple distance measures (MV, MH, DG, EJK), pp. 216–225.

MLDM-2003-TanakaU #analysis #component #multi #principle #using

Discover Motifs in Multi-dimensional Time-Series Using the Principal Component Analysis and the MDL Principle (YT, KU), pp. 252–265.

CAV-2003-Drusinsky #monitoring

Monitoring Temporal Rules Combined with Time Series (DD), pp. 114–117.

DATE-2002-GoffioulWVD #analysis #approach #architecture #using

Analysis of Nonlinearities in RF Front-End Architectures Using a Modified Volterra Series Approach (MG, PW, GV, SD), pp. 352–356.

SIGMOD-2002-GaoW #query #similarity #streaming

Continually evaluating similarity-based pattern queries on a streaming time series (LG, XSW), pp. 370–381.

SIGMOD-2002-MoonWH #database #sequence

General match: a subsequence matching method in time-series databases based on generalized windows (YSM, KYW, WSH), pp. 382–393.

VLDB-2002-ChenHWW #analysis #data type #multi

Multi-Dimensional Regression Analysis of Time-Series Data Streams (YC, GD, JH, BWW, JW), pp. 323–334.

ICSM-2002-FuentetajaB #evolution #perspective

Software Evolution from a Time-Series Perspective (EF, DJB), pp. 226–229.

CAiSE-2002-LeeKL #data-driven #database #distance #performance #similarity

Efficient Similarity Search for Time Series Data Based on the Minimum Distance (SL, DK, SL), pp. 377–391.

CIKM-2002-GaoYW #nearest neighbour #query #streaming

Evaluating continuous nearest neighbor queries for streaming time series via pre-fetching (LG, ZY, XSW), pp. 485–492.

CIKM-2002-MotoyoshiMW #mining

Mining temporal classes from time series data (MM, TM, KW), pp. 493–498.

KDD-2002-JinLS #similarity

Similarity measure based on partial information of time series (XJ, YL, CS), pp. 544–549.

KDD-2002-KeoghK #benchmark #bibliography #data mining #empirical #metric #mining #on the

On the need for time series data mining benchmarks: a survey and empirical demonstration (EJK, SK), pp. 102–111.

KDD-2002-KeoghLC #database #linear

Finding surprising patterns in a time series database in linear time and space (EJK, SL, BYcC), pp. 550–556.

KDD-2002-YamanishiT #detection #framework

A unifying framework for detecting outliers and change points from non-stationary time series data (KY, JiT), pp. 676–681.

TOOLS-USA-2002-PatelPS #object-oriented

Object Oriented Extension to Time Series Model (DP, SP, PS), pp. 159–171.

RE-2002-HardtMB #development #requirements

Integrating ECUs in Vehicles — Requirements Engineering in Series Development (MH, RM, JB), pp. 227–236.

SAC-2002-KimYPK #database #retrieval #sequence

Shape-based retrieval of similar subsequences in time-series databases (SWK, JY, SP, THK), pp. 438–445.

ICSM-2001-AntoniolCPM #evolution #modelling

Modeling Clones Evolution through Time Series (GA, GC, MDP, EM), pp. 273–280.

STOC-2001-Kosaraju #graph #parallel

Euler paths in series parallel graphs (SRK), pp. 237–240.

DLT-2001-EsikN #automaton

Automata on Series-Parallel Biposets (ZÉ, ZLN), pp. 217–227.

ICALP-2001-DrosteZ

Rational Transformations of Formal Power Series (MD, GQZ), pp. 555–566.

CIKM-2001-PollyW #feature model #pattern matching #performance #robust

Efficient and Robust Feature Extraction and Pattern Matching of Time Series by a Lattice Structure (WPMP, MHW), pp. 271–278.

ICML-2001-SarkarL #fuzzy #similarity

Application of Fuzzy Similarity-Based Fractal Dimensions to Characterize Medical Time Series (MS, TYL), pp. 465–472.

ICML-2001-SebastianiR #clustering

Clustering Continuous Time Series (PS, MR), pp. 497–504.

VLDB-2000-KoudasIM #identification #roadmap #set #sketching #using

Identifying Representative Trends in Massive Time Series Data Sets Using Sketches (PI, NK, SM), pp. 363–372.

ICALP-2000-Kuske #infinity #logic

Infinite Series-Parallel Posets: Logic and Languages (DK), pp. 648–662.

CIKM-2000-LohKW #approach #database #normalisation #sequence

Index Interpolation: An Approach to Subsequence Matching Supporting Normalization Transform in Time-Series Databases (WKL, SWK, KYW), pp. 480–487.

CIKM-2000-WuAA00a #comparison #database #similarity

A Comparison of DFT and DWT based Similarity Search in Time-Series Databases (YLW, DA, AEA), pp. 488–495.

ICPR-v2-2000-PolickerG #algorithm #clustering #fuzzy #predict

A New Algorithm for Time Series Prediction by Temporal Fuzzy Clustering (SP, ABG), pp. 2728–2731.

KDD-2000-Caraca-ValenteL

Discovering similar patterns in time series (JPCV, ILC), pp. 497–505.

KDD-2000-GeS #markov #pattern matching

Deformable Markov model templates for time-series pattern matching (XG, PS), pp. 81–90.

KDD-2000-YangWY #mining

Mining asynchronous periodic patterns in time series data (JY, WW, PSY), pp. 275–279.

PODS-1999-ChuW #performance #scalability

Fast Time-Series Searching with Scaling and Shifting (KKWC, MHW), pp. 237–248.

VLDB-1999-KoudasMJ #database #mining

Mining Deviants in a Time Series Database (HVJ, NK, SM), pp. 102–113.

DLT-1999-Petre #on the

On semilinearity in formal power series (IP), pp. 220–231.

ICALP-1999-Rutten #automaton #induction

Automata, Power Series, and Coinduction: Taking Input Derivatives Seriously (JJMMR), pp. 645–654.

ICEIS-1999-Habrant #database #learning #network #predict #search-based

Structure Learning of Bayesian Networks from Databases by Genetic Algorithms-Application to Time Series Prediction in Finance (JH), pp. 225–231.

ICML-1999-BontempiBB #learning #predict

Local Learning for Iterated Time-Series Prediction (GB, MB, HB), pp. 32–38.

ICML-1999-Kadous #learning #multi

Learning Comprehensible Descriptions of Multivariate Time Series (MWK), pp. 454–463.

KDD-1999-GuralnikS #detection

Event Detection from Time Series Data (VG, JS), pp. 33–42.

KDD-1999-HuangY #adaptation #query

Adaptive Query Processing for Time-Series Data (YWH, PSY), pp. 282–286.

KDD-1999-Oates #clustering #identification #multi #sequence

Identifying Distinctive Subsequences in Multivariate Time Series by Clustering (TO), pp. 322–326.

SIGIR-1999-KeoghP #feedback #retrieval

Relevance Feedback Retrieval of Time Series Data (EJK, MJP), pp. 183–190.

CIKM-1998-QuWW #multi #performance

Supporting Fast Search in Time Series for Movement Patterns in Multiple Scales (YQ, CW, XSW), pp. 251–258.

ICPR-1998-SinghS #pattern matching

A pattern matching tool for time-series forecasting (SS, ES), pp. 103–105.

ICPR-1998-WuSK #gesture #image #recognition

Spotting recognition of head gestures from color image series (HW, TS, HK), pp. 83–85.

KDD-1998-DasLMRS

Rule Discovery from Time Series (GD, KIL, HM, GR, PS), pp. 16–22.

KDD-1998-KeoghP #classification #clustering #feedback #performance #representation

An Enhanced Representation of Time Series Which Allows Fast and Accurate Classification, Clustering and Relevance Feedback (EJK, MJP), pp. 239–243.

KDD-1998-RaoRC #adaptation #multi

Time Series Forecasting from High-Dimensional Data with Multiple Adaptive Layers (RBR, SR, FC), pp. 319–323.

SIGMOD-1997-RafieiM #query #similarity

Similarity-Based Queries for Time Series Data (DR, AOM), pp. 13–25.

DLT-1997-Kuich97a

Formal Power Series over Trees (WK), pp. 61–101.

ICALP-1997-DrosteG #on the

On Recognizable and Rational Formal Power Series in Partially Commuting Variables (MD, PG), pp. 682–692.

KDD-1997-DeCoste #behaviour #mining #multi

Mining Multivariate Time-Series Sensor Data to Discover Behavior Envelopes (DD), pp. 151–154.

KDD-1997-KeoghS #approach #database #pattern matching #performance #probability

A Probabilistic Approach to Fast Pattern Matching in Time Series Databases (EJK, PS), pp. 24–30.

RTA-1997-BechetGR #axiom #partial order

A Complete Axiomatisation for the Inclusion of Series-Parallel Partial Orders (DB, PdG, CR), pp. 230–240.

WIA-1996-BoneDGM #automaton #finite

Time Series Forecasting by Finite-State Automata (RB, CD, AG, DM), pp. 26–34.

AKDDM-1996-BerndtC #approach #programming

Finding Patterns in Time Series: A Dynamic Programming Approach (DJB, JC), pp. 229–248.

ICPR-1996-Chernov #theorem

Tauber theorems for Dirichlet series and fractals (VMC), pp. 656–661.

SIGMOD-1995-DreyerDS #using

Using the CALANDA Time Series Management System (WD, AKD, DS), p. 489.

VLDB-1995-AgrawalLSS #database #performance #scalability #similarity

Fast Similarity Search in the Presence of Noise, Scaling, and Translation in Time-Series Databases (RA, KIL, HSS, KS), pp. 490–501.

DAC-1994-Nishimukai

Hitachi-PA/50, SH Series Microcontroller (TN), pp. 592–593.

SIGMOD-1994-FaloutsosRM #database #performance #sequence

Fast Subsequence Matching in Time-Series Databases (CF, MR, YM), pp. 419–429.

KDD-1994-BerndtC #using

Using Dynamic Time Warping to Find Patterns in Time Series (DJB, JC), pp. 359–370.

CSM-1993-Winston #standard

Impact of the ISO 9000 Standard Series (ABW), pp. 231–232.

DLT-1993-Honkala #on the

On Lindenmayerian Series in Complete Semirings (JH), pp. 179–192.

DLT-1993-Kuich

Lindenmayer Systems Generalized to Formal Power Series and Their Growth Functions (WK), pp. 171–178.

ICALP-1993-Dumas #algebra #aspect-oriented

Algebraic Aspects of B-regular Series (PD), pp. 457–468.

ICALP-1992-Krob #decidability #multi #problem #similarity

The Equality Problem for Rational Series with Multiplicities in the Tropical Semiring is Undecidable (DK), pp. 101–112.

CADE-1992-WalshNB #proving #theorem proving

The Use of Proof Plans to Sum Series (TW, AN, AB), pp. 325–339.

ICALP-1988-LingasS #algorithm #graph #morphism #polynomial

A Polynomial-Time Algorithm for Subgraph Isomorphism of Two-Connected Series-Parallel Graphs (AL, MMS), pp. 394–409.

PLDI-1987-Waters #performance

Efficient interpretation of synchronizable series expressions (RCW), pp. 74–85.

ICALP-1987-Muller #complexity

Uniform Computational Complexity of Taylor Series (NTM), pp. 435–444.

OOPSLA-1987-KerrP #analysis #object-oriented #programming

Use of Object-Oriented Programming in a Time Series Analysis System (RKK, DBP), pp. 1–10.

SIGMOD-1986-GardarinM #database #evaluation #logic programming #recursion #source code

Evaluation of Database Recursive Logic Programs as Recurrent Function Series (GG, CdM), pp. 177–186.

DAC-1985-OgiharaSM #automation #generative #named #parametricity #testing

PATEGE: an automatic DC parametric test generation system for series gated ECL circuits (TO, SS, SM), pp. 212–218.

STOC-1979-ValdesTL #graph #parallel #recognition

The recognition of Series Parallel digraphs (JV, RET, ELL), pp. 1–12.

STOC-1973-Teitelbaum #algebra #analysis #evaluation #fault

Context-Free Error Analysis by Evaluation of Algebraic Power Series (RT), pp. 196–199.

STOC-1971-Stanat #formal method

Formal Languages and Power Series (DFS), pp. 1–11.

DAC-1970-Hayashi #automation #design

FACOM 230-series computer design automation system (TH), pp. 230–242.