BibSLEIGH corpus
BibSLEIGH tags
BibSLEIGH bundles
BibSLEIGH people
Open Knowledge
XHTML 1.0 W3C Rec
CSS 2.1 W3C CanRec
email twitter
Used together with:
invest (8)
predict (5)
data (4)
function (3)
time (3)

Stem return$ (all stems)

43 papers:

ICEISICEIS-v2-2015-McharfiADBK #product line #traceability
Return on Investment of Software Product Line Traceability in the Short, Mid and Long Term (ZM, BEA, ID, AB, AK), pp. 463–468.
ICEISICEIS-v2-2015-ValenteAN #design #towards
Improving Software Design Decisions towards Enhanced Return of Investment (PV, DA, NJN), pp. 388–394.
SANERCSMR-WCRE-2014-KimuraHHIK #matter #null #question
Does return null matter? (SK, KH, YH, HI, SK), pp. 244–253.
KDDKDD-2014-KapoorSSY #approach #predict
A hazard based approach to user return time prediction (KK, MS, JS, TY), pp. 1719–1728.
VLDBVLDB-2012-DallachiesaNMP #nondeterminism #similarity
Uncertain Time-Series Similarity: Return to the Basics (MD, BN, KM, TP), pp. 1662–1673.
STOCSTOC-2012-DevanurJ #online
Online matching with concave returns (NRD, KJ), pp. 137–144.
CIKMCIKM-2012-WuJZ #behaviour
Serial position effects of clicking behavior on result pages returned by search engines (MW, SJ, YZ), pp. 2411–2414.
KDDKDD-2012-Holada #low cost
Maximizing return and minimizing cost with the right decision management systems (RH), p. 407.
PEPMPEPM-2011-Caballero #functional #logic programming #program transformation #source code
A program transformation for returning states in functional-logic programs (RC), pp. 111–120.
CHICHI-2011-AndersonDB #performance
Diminishing returns?: revisiting perception of computing performance (GJA, RD, EB), pp. 2703–2706.
CHICHI-2010-ShastriFBTP #process
O job can you return my mojo: improving human engagement and enjoyment in routine activities (DS, YF, RB, PT, IP), pp. 2491–2498.
ICMLICML-2010-MorimuraSKHT #approximate #learning #parametricity
Nonparametric Return Distribution Approximation for Reinforcement Learning (TM, MS, HK, HH, TT), pp. 799–806.
RERE-2010-MavinW #approach #requirements
Big Ears (The Return of “Easy Approach to Requirements Engineering”) (AM, PW), pp. 277–282.
ICFPICFP-2009-MidtgaardJ #abstract interpretation #analysis #control flow
Control-flow analysis of function calls and returns by abstract interpretation (JM, TPJ), pp. 287–298.
WCREWCRE-2008-HenrardRCH #experience #re-engineering #scalability
Large-Scale Data Reengineering: Return from Experience (JH, DR, AC, JLH), pp. 305–308.
CIAACIAA-2008-InabaHM #metaprogramming #multi #transducer
Multi-Return Macro Tree Transducers (KI, HH, SM), pp. 102–111.
AdaSIGAda-2008-Taft #ada #implementation
Implementing the extended return statement for Ada 2005 (STT), pp. 97–104.
SEKESEKE-2008-MatalongaG #analysis #fault
Linking Return on Training Investment with Defects Causal Analysis (SM, TSFG), pp. 42–47.
ECOOPECOOP-2008-Guerraoui #transaction
The Return of Transactions (RG), p. 1.
HTHT-2007-Goble #web
The return of the prodigal web: 1 (CAG), p. 2.
SIGMODSIGMOD-2007-LiuC #identification #keyword #xml
Identifying meaningful return information for XML keyword search (ZL, YC), pp. 329–340.
QAPLQAPL-2006-SingerB #predict
Return Value Prediction meets Information Theory (JS, GB), pp. 137–151.
ICSEICSE-2006-RundleD #agile #using
Using return on investment to compare agile and plan-driven practices in undergraduate group projects (PJR, RGD), pp. 649–654.
SPLCSPLC-2006-GanesanMY #predict #product line
Predicting Return-on-Investment for Product Line Generations (DG, DM, KY), pp. 13–22.
ICDARICDAR-2005-RangoniB #categorisation #documentation #logic #recognition
Data categorization for a context return applied to logical document structure recognition (YR, AB), pp. 297–301.
Returning Modified Rows — SELECT Statements with Side Effects (AB, SR, RS), pp. 987–997.
TACASTACAS-2004-AlurEM #logic
A Temporal Logic of Nested Calls and Returns (RA, KE, PM), pp. 467–481.
ICFPICFP-2004-ShiversF #multi
Multi-return function call (OS, DF), pp. 79–89.
Return on investment and organizational adoption (JG), pp. 324–327.
RERE-2004-Cleland-HuangZL #requirements #traceability
A Heterogeneous Solution for Improving the Return on Investment of Requirements Traceability (JCH, GZ, WL), pp. 230–239.
MLDMMLDM-2003-ChiuX #mining #optimisation
Optimizing Financial Portfolios from the Perspective of Mining Temporal Structures of Stock Returns (KCC, LX), pp. 266–275.
ICALPICALP-2002-AkcogluDK #performance
Fast Universalization of Investment Strategies with Provably Good Relative Returns (KA, PD, MYK), pp. 888–900.
ICEISICEIS-v1-2001-BettoniF #assessment
The First Tax Return Assessment Expert System in Switzerland (MCB, GF), pp. 391–396.
Many Happy Returns (OD), p. 1.
STOCSTOC-1999-ChenKLW #bound
Optimal Buy-and-Hold Strategies for Financial Markets with Bounded Daily Returns (GHC, MYK, YDL, HKW), pp. 119–128.
PADLPADL-1999-Schmidt #declarative #design
A Return to Elegance: The Reapplication of Declarative Notation to Software Design (DAS), pp. 360–364.
PEPMPEPM-1997-HornofN #analysis #imperative
Accurate Binding-Time Analysis For Imperative Languages: Flow, Context, and Return Sensitivity (LH, JN), pp. 63–73.
CSCWCSCW-1996-Greenbaum #case study #process
Back to Labor: Returning to Labor Process Discussions in the Study of Work (JG), pp. 229–237.
KDDAKDDM-1996-ApteH #predict
Predicting Equity Returns from Securities Data (CA, SJH), pp. 541–560.
ICMLICML-1996-PendrithR #difference #learning
Actual Return Reinforcement Learning versus Temporal Differences: Some Theoretical and Experimental Results (MDP, MRKR), pp. 373–381.
LISPLFP-1994-AshleyD #implementation #multi #performance
An Efficient Implementation of Multiple Return Values in Scheme (JMA, RKD), pp. 140–149.
KDDKDD-1994-ApteH #generative #predict
Predicting Equity Returns from Securities Data with Minimal Rule Generation (CA, SJH), pp. 407–418.
The Effects of New Information Technology on Interorganizational Relations: Electronic Tax Return Lodgement in Australia (TAW), pp. 356–361.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
Hosted as a part of SLEBOK on GitHub.