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Classifying and Ranking: The First Step Towards Mining Inside Vertical Search Engines.

Authors :
Hutchison, David
Kanade, Takeo
Kittler, Josef
Kleinberg, Jon M.
Mattern, Friedemann
Mitchell, John C.
Naor, Moni
Nierstrasz, Oscar
Pandu Rangan, C.
Steffen, Bernhard
Sudan, Madhu
Terzopoulos, Demetri
Tygar, Doug
Vardi, Moshe Y.
Weikum, Gerhard
Wagner, Roland
Revell, Norman
Pernul, Günther
Hang Guo
Jun Zhang
Source :
Database & Expert Systems Applications (9783540744672); 2007, p223-232, 10p
Publication Year :
2007

Abstract

Vertical Search Engines (VSEs), which usually work on specific domains, are designed to answer complex queries of professional users. VSEs usually have large repositories of structured instances. Traditional instance ranking methods do not consider the categories that instances belong to. However, users of different interests usually care only the ranking list in their own communities. In this paper we design a ranking algorithm -ZRank, to rank the classified instances according to their importances in specific categories. To test our idea, we develop a scientific paper search engine-CPaper. By employing instance classifying and ranking algorithms, we discover some helpful facts to users of different interests. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540744672
Database :
Complementary Index
Journal :
Database & Expert Systems Applications (9783540744672)
Publication Type :
Book
Accession number :
33316712
Full Text :
https://doi.org/10.1007/978-3-540-74469-6_23