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» Mining clickthrough data for collaborative web search
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KDD
2003
ACM
129views Data Mining» more  KDD 2003»
15 years 10 months ago
Nantonac collaborative filtering: recommendation based on order responses
A recommender system suggests the items expected to be preferred by the users. Recommender systems use collaborative filtering to recommend items by summarizing the preferences of...
Toshihiro Kamishima
KDD
2005
ACM
180views Data Mining» more  KDD 2005»
15 years 3 months ago
Information retrieval based on collaborative filtering with latent interest semantic map
In this paper, we propose an information retrieval model called Latent Interest Semantic Map (LISM), which features retrieval composed of both Collaborative Filtering(CF) and Prob...
Noriaki Kawamae, Katsumi Takahashi
WSDM
2012
ACM
207views Data Mining» more  WSDM 2012»
13 years 5 months ago
Domain bias in web search
This paper uncovers a new phenomenon in web search that we call domain bias — a user’s propensity to believe that a page is more relevant just because it comes from a particul...
Samuel Ieong, Nina Mishra, Eldar Sadikov, Li Zhang
KDD
2004
ACM
146views Data Mining» more  KDD 2004»
15 years 10 months ago
Using Hyperlink Features to Personalize Web Search
Personalized search has gained great popularity to improve search effectiveness in recent years. The objective of personalized search is to provide users with information tailored ...
Mehmet S. Aktas, Mehmet A. Nacar, Filippo Menczer
WSDM
2009
ACM
198views Data Mining» more  WSDM 2009»
15 years 4 months ago
Measuring the similarity between implicit semantic relations using web search engines
Measuring the similarity between implicit semantic relations is an important task in information retrieval and natural language processing. For example, consider the situation whe...
Danushka Bollegala, Yutaka Matsuo, Mitsuru Ishizuk...