Learning to Rank in Vector Spaces and Social Networks
نویسندگان
چکیده
منابع مشابه
Learning to Rank in Vector Spaces and Social Networks
User query q, Web pages {v } (q, v) can be represented with a rich feature vector Text match score with title, anchor text, headings, bold text, body text,. .. , of v as a hypertext document Pagerank, topic-specific Pageranks, personalized Pageranks of v as a node in the Web graph Estimated location of user, commercial intent,. .. Must we guess the relative importance of these features? How to ...
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ژورنال
عنوان ژورنال: Internet Mathematics
سال: 2007
ISSN: 1542-7951,1944-9488
DOI: 10.1080/15427951.2007.10129291