BibSLEIGH — Alan

Travelled to:

1 × Japan
1 × Spain
1 × Switzerland
1 × The Netherlands
1 × United Kingdom
2 × China
2 × Ireland
3 × USA

Collaborated with:

M.Larson Y.Shi A.Karatzoglou L.Baltrunas S.Rudinac B.Loni P.Xu D.M.J.Tax N.Oliver C.Kofler A.Said X.Zhao J.Wang

Talks about:

collabor (6) filter (6) recommend (4) factor (4) base (4) awar (4) context (3) video (3) learn (3) user (3)

Person: Alan Hanjalic

DBLP: Hanjalic:Alan

Contributed to:

2014

2013

2012

2011

2010

2009

Wrote 15 papers:

CIKM-2014-ShiKBLH #learning #named #recommendation: CARS2: Learning Context-aware Representations for Context-aware Recommendations (YS, AK, LB, ML, AH), pp. 291–300.
ECIR-2014-LoniSLH #collaboration: Cross-Domain Collaborative Filtering with Factorization Machines (BL, YS, ML, AH), pp. 656–661.
RecSys-2014-LoniSLH #collaboration: “Free lunch” enhancement for collaborative filtering with factorization machines (BL, AS, ML, AH), pp. 281–284.
RecSys-2013-ShiKBLH #multi #named #optimisation #rank: xCLiMF: optimizing expected reciprocal rank for data with multiple levels of relevance (YS, AK, LB, ML, AH), pp. 431–434.
ICPR-2012-XuTH #categorisation #representation #video #web: A structure-based video representation for web video categorization (PX, DMJT, AH), pp. 433–436.
RecSys-2012-ShiKBLOH #collaboration #learning #named #rank: CLiMF: learning to maximize reciprocal rank with collaborative less-is-more filtering (YS, AK, LB, ML, NO, AH), pp. 139–146.
SIGIR-2012-ShiKBLHO #named #optimisation #recommendation: TFMAP: optimizing MAP for top-n context-aware recommendation (YS, AK, LB, ML, AH, NO), pp. 155–164.
SIGIR-2012-ShiZWLH #adaptation #recommendation: Adaptive diversification of recommendation results via latent factor portfolio (YS, XZ, JW, ML, AH), pp. 175–184.
ECIR-2011-KoflerLH #internet #video: To Seek, Perchance to Fail: Expressions of User Needs in Internet Video Search (CK, ML, AH), pp. 611–616.
ECIR-2011-ShiLH #collaboration #multi #ranking #self: Reranking Collaborative Filtering with Multiple Self-contained Modalities (YS, ML, AH), pp. 699–703.
ECIR-2011-ShiLH11a #how #question #recommendation #trust: How Far Are We in Trust-Aware Recommendation? (YS, ML, AH), pp. 704–707.
ECIR-2010-RudinacLH #consistency #query #retrieval: Exploiting Result Consistency to Select Query Expansions for Spoken Content Retrieval (SR, ML, AH), pp. 645–648.
RecSys-2010-ShiLH #collaboration #learning #matrix #rank: List-wise learning to rank with matrix factorization for collaborative filtering (YS, ML, AH), pp. 269–272.
SIGIR-2010-RudinacLH #concept #query #retrieval #visual notation: Visual concept-based selection of query expansions for spoken content retrieval (SR, ML, AH), pp. 891–892.
RecSys-2009-ShiLH #collaboration #similarity: Exploiting user similarity based on rated-item pools for improved user-based collaborative filtering (YS, ML, AH), pp. 125–132.