Proceedings of the Second Conference on Recommender Systems
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Pearl Pu, Derek G. Bridge, Bamshad Mobasher, Francesco Ricci
Proceedings of the Second Conference on Recommender Systems
RecSys, 2008.

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@proceedings{RecSys-2008,
	address       = "Lausanne, Switzerland",
	editor        = "Pearl Pu and Derek G. Bridge and Bamshad Mobasher and Francesco Ricci",
	isbn          = "978-1-60558-093-7",
	publisher     = "{ACM}",
	title         = "{Proceedings of the Second Conference on Recommender Systems}",
	year          = 2008,
}

Contents (51 items)

RecSys-2008-Broder #recommendation
Computational advertising and recommender systems (AZB), pp. 1–2.
RecSys-2008-DingZYZFB #collaboration #fault #predict #statistics
Boosting collaborative filtering based on statistical prediction errors (SD, SZ, QY, XZ, RF, LDB), pp. 3–10.
RecSys-2008-ParkT #how #recommendation
The long tail of recommender systems and how to leverage it (YJP, AT), pp. 11–18.
RecSys-2008-GunawardanaM #recommendation
Tied boltzmann machines for cold start recommendations (AG, CM), pp. 19–26.
RecSys-2008-SchifanellaPGR #ad hoc #collaboration #mobile #named #network #self
MobHinter: epidemic collaborative filtering and self-organization in mobile ad-hoc networks (RS, AP, CG, GR), pp. 27–34.
RecSys-2008-ShaniCM #mining #recommendation #web
Mining recommendations from the web (GS, DMC, CM), pp. 35–42.
RecSys-2008-SymeonidisNM #recommendation #reduction
Tag recommendations based on tensor dimensionality reduction (PS, AN, YM), pp. 43–50.
RecSys-2008-ZanardiC #ranking #recommendation #social #using
Social ranking: uncovering relevant content using tag-based recommender systems (VZ, LC), pp. 51–58.
RecSys-2008-GeyerDMMF #online #recommendation #self #topic
Recommending topics for self-descriptions in online user profiles (WG, CD, DRM, MJM, JF), pp. 59–66.
RecSys-2008-GargW #interactive #personalisation #recommendation
Personalized, interactive tag recommendation for flickr (NG, IW), pp. 67–74.
RecSys-2008-ChenP #evaluation #interface #recommendation
A cross-cultural user evaluation of product recommender interfaces (LC, PP), pp. 75–82.
RecSys-2008-XuJL #documentation #image #online #personalisation #recommendation #video
Personalized online document, image and video recommendation via commodity eye-tracking (SX, HJ, FCML), pp. 83–90.
RecSys-2008-MaidelSST #evaluation #personalisation
Evaluation of an ontology-content based filtering method for a personalized newspaper (VM, PS, BS, MTM), pp. 91–98.
RecSys-2008-WuWC #analysis #automation #incremental #probability #recommendation #semantics
Incremental probabilistic latent semantic analysis for automatic question recommendation (HW, YW, XC), pp. 99–106.
RecSys-2008-LiWZZC #named #parallel #query #recommendation
Pfp: parallel fp-growth for query recommendation (HL, YW, DZ, MZ, EYC), pp. 107–114.
RecSys-2008-HadzicO #graph #navigation
Critique graphs for catalogue navigation (TH, BO), pp. 115–122.
RecSys-2008-ZhangH #recommendation
Avoiding monotony: improving the diversity of recommendation lists (MZ, NH), pp. 123–130.
RecSys-2008-YildirimK #collaboration #problem #random
A random walk method for alleviating the sparsity problem in collaborative filtering (HY, MSK), pp. 131–138.
RecSys-2008-Zanker #collaboration #constraints #recommendation
A collaborative constraint-based meta-level recommender (MZ), pp. 139–146.
RecSys-2008-ResnickS #recommendation
The information cost of manipulation-resistance in recommender systems (PR, RS), pp. 147–154.
RecSys-2008-BryanOC #collaboration #recommendation #retrieval
Unsupervised retrieval of attack profiles in collaborative recommender systems (KB, MPO, PC), pp. 155–162.
RecSys-2008-DegemmisLSB #recommendation #semantics
Integrating tags in a semantic content-based recommender (MD, PL, GS, PB), pp. 163–170.
RecSys-2008-BrodskyHW #framework #named #recommendation
CARD: a decision-guidance framework and application for recommending composite alternatives (AB, SMH, JW), pp. 171–178.
RecSys-2008-CelmaH #approach #novel #recommendation
A new approach to evaluating novel recommendations (ÒC, PH), pp. 179–186.
RecSys-2008-DrennerST #community #experience #user interface
Crafting the initial user experience to achieve community goals (SD, SS, LGT), pp. 187–194.
RecSys-2008-KagieWG #difference #using
Choosing attribute weights for item dissimilarity using clikstream data with an application to a product catalog map (MK, MCvW, PJFG), pp. 195–202.
RecSys-2008-KoutrikaIBG #flexibility #recommendation
Flexible recommendations over rich data (GK, RI, BB, HGM), pp. 203–210.
RecSys-2008-KrishnanNNDK #online #predict #recommendation
Who predicts better?: results from an online study comparing humans and an online recommender system (VK, PKN, MN, RTD, JAK), pp. 211–218.
RecSys-2008-LakiotakiTM #analysis #multi #named #recommendation
UTA-Rec: a recommender system based on multiple criteria analysis (KL, ST, NFM), pp. 219–226.
RecSys-2008-LathiaHC #network #social
kNN CF: a temporal social network (NL, SH, LC), pp. 227–234.
RecSys-2008-OostendorpR #interface #recommendation #reduction
Three recommender approaches to interface controls reduction (NO, PR), pp. 235–242.
RecSys-2008-Recio-GarciaDG #prototype #recommendation
Prototyping recommender systems in jcolibri (JARG, BDA, PAGC), pp. 243–250.
RecSys-2008-RendleS #kernel #matrix #modelling #recommendation #scalability
Online-updating regularized kernel matrix factorization models for large-scale recommender systems (SR, LST), pp. 251–258.
RecSys-2008-ShepitsenGMB #clustering #personalisation #recommendation #social #using
Personalized recommendation in social tagging systems using hierarchical clustering (AS, JG, BM, RDB), pp. 259–266.
RecSys-2008-TakacsPNT #algorithm #matrix #problem
Matrix factorization and neighbor based algorithms for the netflix prize problem (GT, IP, BN, DT), pp. 267–274.
RecSys-2008-WeimerKS #adaptation #collaboration
Adaptive collaborative filtering (MW, AK, AJS), pp. 275–282.
RecSys-2008-AgrahriMR #people #question
Can people collaborate to improve the relevance of search results? (AKA, DATM, JR), pp. 283–286.
RecSys-2008-BogersB #recommendation #using
Recommending scientific articles using citeulike (TB, AvdB), pp. 287–290.
RecSys-2008-DiasLLEL #case study #personalisation #recommendation
The value of personalised recommender systems to e-business: a case study (MBD, DL, ML, WED, PJGL), pp. 291–294.
RecSys-2008-Baltrunas #information management #recommendation
Exploiting contextual information in recommender systems (LB), pp. 295–298.
RecSys-2008-Domingues #adaptation #analysis #framework #independence #monitoring #platform #web
An independent platform for the monitoring, analysis and adaptation of web sites (MAD), pp. 299–302.
RecSys-2008-DrachslerHK #learning #navigation
Navigation support for learners in informal learning environments (HD, HGKH, RK), pp. 303–306.
RecSys-2008-Kwon #rating #recommendation #using
Improving top-n recommendation techniques using rating variance (YK), pp. 307–310.
RecSys-2008-Lee #named #recommendation #trust
PITTCULT: trust-based cultural event recommender (DHL), pp. 311–314.
RecSys-2008-Sampaio #internet #network #performance #process #recommendation
A network performance recommendation process for advanced internet applications users (LNS), pp. 315–318.
RecSys-2008-Santos #adaptation #lifecycle #recommendation #standard
A recommender system to provide adaptive and inclusive standard-based support along the elearning life cycle (OCS), pp. 319–322.
RecSys-2008-Teppan #recommendation
Implications of psychological phenomenons for recommender systems (ECT), pp. 323–326.
RecSys-2008-Umyarov #performance #predict #recommendation
Leveraging aggregate ratings for improving predictive performance of recommender systems (AU), pp. 327–330.
RecSys-2008-Burke #recommendation #robust
Robust recommender systems (RDB), pp. 331–332.
RecSys-2008-Koren #collaboration #tutorial
Tutorial on recent progress in collaborative filtering (YK), pp. 333–334.
RecSys-2008-AdomaviciusT #recommendation
Context-aware recommender systems (GA, AT), pp. 335–336.

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