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» Learning block importance models for web pages
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WWW
2005
ACM
14 years 8 months ago
Adaptive page ranking with neural networks
Recent developments in the area of neural networks provided new models which are capable of processing general types of graph structures. Neural networks are well-known for their ...
Franco Scarselli, Sweah Liang Yong, Markus Hagenbu...
JCIT
2010
182views more  JCIT 2010»
13 years 2 months ago
CT-Rank: A Time-aware Ranking Algorithm for Web Search
Time plays important roles in Web search, because most Web pages contain time information and a lot of Web queries are time-related. However, traditional search engines such as Go...
Peiquan Jin, Xiaowen Li, Hong Chen, Lihua Yue
WEBDB
2009
Springer
149views Database» more  WEBDB 2009»
14 years 2 months ago
Extracting Route Directions from Web Pages
Linguists and geographers are more and more interested in route direction documents because they contain interesting motion descriptions and language patterns. A large number of s...
Xiao Zhang, Prasenjit Mitra, Sen Xu, Anuj R. Jaisw...
CIKM
2003
Springer
14 years 23 days ago
Categorizing web queries according to geographical locality
Web pages (and resources, in general) can be characterized according to their geographical locality. For example, a web page with general information about wildflowers could be c...
Luis Gravano, Vasileios Hatzivassiloglou, Richard ...
WWW
2002
ACM
14 years 8 months ago
Topic-sensitive PageRank
In the original PageRank algorithm for improving the ranking of search-query results, a single PageRank vector is computed, using the link structure of the Web, to capture the rel...
Taher H. Haveliwala