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CISS
2008
IEEE
15 years 4 months ago
A lower-bound on the number of rankings required in recommender systems using collaborativ filtering
— We consider the situation where users rank items from a given set, and each user ranks only a (small) subset of all items. We assume that users can be classified into C classe...
Peter Marbach
ICDM
2010
IEEE
121views Data Mining» more  ICDM 2010»
14 years 7 months ago
Recommending Social Events from Mobile Phone Location Data
A city offers thousands of social events a day, and it is difficult for dwellers to make choices. The combination of mobile phones and recommender systems can change the way one de...
Daniele Quercia, Neal Lathia, Francesco Calabrese,...
EMNLP
2007
14 years 11 months ago
What is the Jeopardy Model? A Quasi-Synchronous Grammar for QA
This paper presents a syntax-driven approach to question answering, specifically the answer-sentence selection problem for short-answer questions. Rather than using syntactic fea...
Mengqiu Wang, Noah A. Smith, Teruko Mitamura
82
Voted
EEE
2005
IEEE
15 years 3 months ago
Feature Selection Methods for Conversational Recommender Systems
This paper focuses on question selection methods for conversational recommender systems. We consider a scenario, where given an initial user query, the recommender system may ask ...
Nader Mirzadeh, Francesco Ricci, Mukesh Bansal
ADAPTIVE
2007
Springer
15 years 3 months ago
Collaborative Filtering Recommender Systems
One of the potent personalization technologies powering the adaptive web is collaborative filtering. Collaborative filtering (CF) is the process of filtering or evaluating items th...
J. Ben Schafer, Dan Frankowski, Jonathan L. Herloc...