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BPR: Bayesian Personalized Ranking from Implicit Feedback, Rendle+, UAI'09

https://arxiv.org/pdf/1205.2618.pdf

DualSum: a Topic-Model based approach for update summarization, Delort et al., [EACL’12]

https://dl.acm.org/citation.cfm?id=2380845

Learning User Profiles from Tagging Data and Leveraging them for Personal(ized) Information Access, Michlmayr+, WWW'07

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.444.7873&rep=rep1&type=pdf

SCENE: A Scalable Two-Stage Personalized News Recommendation System, Li et al., SIGIR’11

https://users.cs.fiu.edu/~taoli/pub/p125-li-sigir2011.pdf

Multi-relational matrix factorization using bayesian personalized ranking for social network data, Krohn-Grimberghe+, WSDM'12

https://www.ismll.uni-hildesheim.de/pub/pdfs/artus_lucas_wsdm2012.pdf

WebInEssence: A Personalized Web-Based Multi-Document Summarization and Recommendation System, Radev+, [NAACL, 01]

http://clair.si.umich.edu/~radev/papers/naacl-summ01.pdf

TimedTextRank: Adding the Temporal Dimension to Multi-Document Summarization, Xiaojun Wan, SIGIR’07

https://pdfs.semanticscholar.org/c4ee/47ace546195a32799ad4a20aa934cd665903.pdf

Document Update Summarization Using Incremental Hierarchical Clustering, Wang et al.,　[CIKM’10]

https://dl.acm.org/citation.cfm?id=1871476

Personalized PageRank based Multi-document summarization, Liu+, [WSCS '08]

http://ieeexplore.ieee.org/document/4570834/

Personalized Summarization Agent Using Non-negative Matrix Factorization, PRICAI, [Park, 2008], 19

https://link.springer.com/chapter/10.1007/978-3-540-89197-0_103

Automatic Personalized Summarization using Non-negative Matrix Factorization and Relevance Measure, IWSCA, [Park+, 2008], 10

http://ieeexplore.ieee.org/document/4573153/

“I like to explore sometimes”: Adapting to Dynamic User Novelty Preferences, Kapoor et al. (with Konstan), [RecSys’15]

https://dl.acm.org/citation.cfm?id=2800172

Personalized Multi-Document Summarization using N-Gram Topic Model Fusion, Hennig+, [SPIM, 2010]

http://www.dai-labor.de/fileadmin/files/publications/spim-plsafusion.pdf

A cognitive model of document use during a research project, Wang and Soergel, 1998

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.124.1822&rep=rep1&type=pdf

Update Summarization using Semi-Supervised Learning Based on Hellinger Distance, Wang et al., CIKM’15

http://delivery.acm.org/10.1145/2810000/2806628/p1907-wang.pdf?ip=131.112.138.2&id=2806628&acc=ACTIVE%20SERVICE&key=D2341B890AD12BFE%2EE857D5F645C75AE5%2E4D4702B0C3E38B35%2E4D4702B0C3E38B35&CFID=840322391&CFTOKEN=91726626&__acm__=1514447714_516102e181849099c8f774336da60b53

Aspect-Based Personalized Text Summarization, Berkovsky+(Tim先生のグループ), AH'2008, 31

https://people.eng.unimelb.edu.au/tbaldwin/pubs/ah2008-summary.pdf

Automatic Text Summarization based on the Global Document Annotation, COLING-ACL, [Nagao+, 1998], 59

http://www.aclweb.org/anthology/P98-2151

A Study for Documents Summarization based on Personal Annotation, HLT-NAACL-DUC’03, [Zhang+, 2003], 33

http://www.aclweb.org/anthology/W03-0506

Comments-Oriented Document Summarization: Understanding Documents with Reader’s Feedback SIGIR’08, [Hu+, 2008]

概要

コメントを利用したブログの要約を提案している最初の論文（CIKM short 07の方が先だけど）
読み手がコメントで議論しているトピックをカバーするような要約を生成するタスク

Segmentation Based, Personalized Web Page Summarization Model, [Journal of advances in information technology, vol. 3, no.3, 2012]

http://www.jait.us/uploadfile/2014/1218/20141218024756960.pdf

Modeling Anchor Text and Classifying Queries to Enhance Web Document Retrieval, WWW’08, [Fujii, 2008]

https://dl.acm.org/citation.cfm?id=1367544

HLTCOE at TREC 2013: Temporal Summarization, Xu et al, [TREC 2013]

http://trec.nist.gov/pubs/trec22/papers/hltcoe-ts.pdf

A semantic-expansion approach to personalized knowledge recommendation, Liang, Yang, Chen and Ku, Decision Support Systems, 2007

http://www.sciencedirect.com/science/article/pii/S0167923607000814

DUC 2007, Update Summarization Dataset

・including two types of summaries

・event titleやnarrativeが含まれている

BJUT at TREC 2013 Temporal Summarization Track, yang et al. [TREC2013]

http://trec.nist.gov/pubs/trec22/papers/BJUT-ts.pdf

A Scalable MMR Approach to Sentence Scoring for Multi-Document Update Summarization, Boudin et al., COLING’08

http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.222.5832

Personalizing Search via Automated Analysis of Interests and Activities, SIGIR, [Teevan+, 2005]

https://dl.acm.org/citation.cfm?id=1076111

Neural Networks for Web Content Filtering, 2002, Lee, Fui and Fong, IEEE Intelligent Systems

https://dl.acm.org/citation.cfm?id=630765

Interactive Recommender Systems

https://www.slideshare.net/MrChrisJohnson/interactive-recommender-systems-with-netflix-and-spotify

Combination of Web page recommender systems, Goksedef, Gunduz-oguducu, Elsevier, 2010

http://www.sciencedirect.com/science/article/pii/S0957417409008276

Collaborative Summarization: When Collaborative Filtering Meets Document Summarization, Qu+, PACLIC'09, 6

http://www.aclweb.org/anthology/Y09-2005

Generating Personalized Summaries Using Publicly Available Web Documents, Kumar+, WI-IAT'08, 18

https://www.researchgate.net/profile/Vasudeva-Varma/publication/221155226_Generating_Personalized_Summaries_Using_Publicly_Available_Web_Documents/links/56cec0f508ae85c8233f9329/Generating-Personalized-Summaries-Using-Publicly-Available-Web-Documents.pdf

Incremental Update Summarization: Adaptive Sentence Selection based on Prevalence and Novelty, McCreadie et al., CIKM’14

https://pdfs.semanticscholar.org/edc8/04b43e70a14e0537bc597f4ad95db34a089e.pdf

Incremental Personalised Summarisation with Novelty Detection, Campana+, FQAS'09, 11

UserModelを表現する際に、従来は単語の集合などが用いられてきたが、これではContextの情報が失われてしまうことを指摘。これを解決するために、sentenceの集合で情報を持っておき、これらから構築されるAffinityGraphをユーザモデルとする手法を提案。さらに、ユーザモデルからとcandidateとの類似度を測る手法も提案（candidateとユーザモデル中のあるノードの類似度と、そのノードと他ノードとの類似度の総和を正規化したdegreeの和の最大値を類似度とする）。