Joseph A. Konstan, John Riedl, Barry Smyth
Proceedings of the First Conference on Recommender Systems
RecSys, 2007.

@proceedings{RecSys-2007,
	address       = "Minneapolis, Minnesota, USA",
	editor        = "Joseph A. Konstan and John Riedl and Barry Smyth",
	isbn          = "978-1-59593-730-8",
	publisher     = "{ACM}",
	title         = "{Proceedings of the First Conference on Recommender Systems}",
	year          = 2007,
}

Contents (38 items)

27 ×#recommendation
7 ×#collaboration
3 ×#clustering
3 ×#distributed
3 ×#hybrid
3 ×#learning
3 ×#social
2 ×#adaptation
2 ×#algorithm
2 ×#approach

RecSys-2007-LathiaHC #collaboration #distributed #metric #using

Private distributed collaborative filtering using estimated concordance measures (NL, SH, LC), pp. 1–8.

RecSys-2007-BerkovskyEKR #collaboration #distributed #privacy

Enhancing privacy and preserving accuracy of a distributed collaborative filtering (SB, YE, TK, FR), pp. 9–16.

RecSys-2007-MassaA #recommendation #trust

Trust-aware recommender systems (PM, PA), pp. 17–24.

RecSys-2007-ResnickS #recommendation

The influence limiter: provably manipulation-resistant recommender systems (PR, RS), pp. 25–32.

RecSys-2007-BerkovskyKR #collaboration #distributed

Distributed collaborative filtering with domain specialization (SB, TK, FR), pp. 33–40.

RecSys-2007-AngladeTV #clustering #identification

Complex-network theoretic clustering for identifying groups of similar listeners in p2p systems (AA, MT, FV), pp. 41–48.

RecSys-2007-MehtaHN #collaboration #robust

Robust collaborative filtering (BM, TH, WN), pp. 49–56.

RecSys-2007-ZhangP #algorithm #collaboration #predict #recommendation #recursion

A recursive prediction algorithm for collaborative filtering recommender systems (JZ, PP), pp. 57–64.

RecSys-2007-BridgeR #editing #query #recommendation

Supporting product selection with query editing recommendations (DGB, FR), pp. 65–72.

RecSys-2007-PronkVPT #classification #naive bayes #recommendation

Incorporating user control into recommender systems based on naive bayesian classification (VP, WFJV, AP, MT), pp. 73–80.

RecSys-2007-NguyenR #evaluation #game studies #interactive #mobile #recommendation

Replaying live-user interactions in the off-line evaluation of critique-based mobile recommendations (QNN, FR), pp. 81–88.

RecSys-2007-ViappianiPF #adaptation #recommendation

Conversational recommenders with adaptive suggestions (PV, PP, BF), pp. 89–96.

RecSys-2007-GadanhoL #nondeterminism

Addressing uncertainty in implicit preferences (SCG, NL), pp. 97–104.

RecSys-2007-SandvigMB #collaboration #mining #recommendation #robust

Robustness of collaborative recommendation based on association rule mining (JJS, BM, RDB), pp. 105–112.

RecSys-2007-TaghipourKG #approach #learning #recommendation #web

Usage-based web recommendations: a reinforcement learning approach (NT, AAK, SSG), pp. 113–120.

RecSys-2007-NguyenDB #induction #recommendation #rule-based

Improving new user recommendations with rule-based induction on cold user data (ATN, ND, CB), pp. 121–128.

RecSys-2007-LiDEL #probability #recommendation

A probabilistic model for item-based recommender systems (ML, MBD, WED, PJGL), pp. 129–132.

RecSys-2007-OMahonyS #online #recommendation

A recommender system for on-line course enrolment: an initial study (MPO, BS), pp. 133–136.

RecSys-2007-LeinoR #recommendation

Case amazon: ratings and reviews as part of recommendations (JL, KJR), pp. 137–140.

RecSys-2007-BogersB #algorithm #information retrieval #recommendation

Comparing and evaluating information retrieval algorithms for news recommendation (TB, AvdB), pp. 141–144.

RecSys-2007-RubensS #collaboration #learning

Influence-based collaborative active learning (NR, MS), pp. 145–148.

RecSys-2007-NathansonBG #adaptation #clustering #recommendation #using

Eigentaste 5.0: constant-time adaptability in a recommender system using item clustering (TN, EB, KYG), pp. 149–152.

RecSys-2007-TintarevM #design #effectiveness #recommendation

Effective explanations of recommendations: user-centered design (NT, JM), pp. 153–156.

RecSys-2007-WinterboerM #recommendation

Evaluating information presentation strategies for spoken recommendations (AW, JDM), pp. 157–160.

RecSys-2007-UmyarovT #recommendation

Leveraging aggregate ratings for better recommendations (AU, AT), pp. 161–164.

RecSys-2007-HarperSF #clustering #recommendation #social

Supporting social recommendations with activity-balanced clustering (FMH, SS, DF), pp. 165–168.

RecSys-2007-ChenP #evaluation #hybrid #recommendation

The evaluation of a hybrid critiquing system with preference-based recommendations organization (LC, PP), pp. 169–172.

RecSys-2007-WebsterV #recommendation

The keepup recommender system (AW, JV), pp. 173–176.

RecSys-2007-TiemannP #hybrid #learning #music #recommendation #towards

Towards ensemble learning for hybrid music recommendation (MT, SP), pp. 177–178.

RecSys-2007-FreyneFC #data access #recommendation #social #towards

Toward the exploitation of social access patterns for recommendation (JF, RF, MC), pp. 179–182.

RecSys-2007-KapoorCBFSRK #named #research

Techlens: a researcher’s desktop (NK, JC, JTB, GCF, JAS, JR, JAK), pp. 183–184.

RecSys-2007-McCarthy #challenge #physics #recommendation

The challenges of recommending digital selves in physical spaces (JFM), pp. 185–186.

RecSys-2007-Donaldson #hybrid #music #recommendation

A hybrid social-acoustic recommendation system for popular music (JD), pp. 187–190.

RecSys-2007-Fu #feedback #web

Evaluating sources of implicit feedback in web searches (XF), pp. 191–194.

RecSys-2007-Lorenzi #approach #knowledge-based #maintenance #multi #recommendation

A multiagent knowledge-based recommender approach with truth maintenance (FL), pp. 195–198.

RecSys-2007-Radmacher #communication #elicitation

Elicitation of profile attributes by transparent communication (MR), pp. 199–202.

RecSys-2007-Tintarev #recommendation

Explanations of recommendations (NT), pp. 203–206.

RecSys-2007-Vuorikari #education #information retrieval #question #reuse #social #using

Can social information retrieval enhance the discovery and reuse of digital educational content? (RV), pp. 207–210.