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Relating Web Pages to Enable Information-Gathering Tasks

by: Amitabha Bagchi, and Garima Lahoti

In: HT '09: Proceedings of the Twentieth ACM Conference on Hypertext and Hypermedia New York, NY, USA: ACM (July 2009) .

Abstract

We argue that relationships between Web pages are functions of the user's intent. We identify a class of Web tasks - information-gathering - that can be facilitated by providing links to pages related to the page the user is currently viewing. We define three kinds of intentional relationships that correspond to whether the user is a seeking sources of information, b reading pages which provide information, or c surfing through pages as part of an extended information-gathering process. We show that these three relationships can be mined using a combination of textual and link information and provide three scoring mechanisms that correspond to them: \em SeekRel, \em FactRel and \em SurfRel. These scoring mechanisms incorporate both textual and link information. We build a set of capacitated subnetworks, each corresponding to a particular keyword. Scores are computed by computing flows on these subnetworks. The capacities of the links are derived from the \em hub and \em authority values of the nodes they connect, following the work of Kleinberg 1998 on assigning authority to pages in hyperlinked environments. We evaluated our scoring mechanism by running experiments on four data sets taken from the Web. We present user evaluations of the relevance of the top results returned by our scoring mechanisms and compare those to the top results returned by Google's Similar Pages feature, and the \em Companion algorithm Dean and Henzinger, 1999.

BibTeX record

@inproceedings{bagchi2009relating,
  abstract = {We argue that relationships between Web pages are functions of the user's intent. We identify a class of Web tasks - information-gathering - that can be facilitated by providing links to pages related to the page the user is currently viewing. We define three kinds of intentional relationships that correspond to whether the user is a) seeking sources of information, b) reading pages which provide information, or c) surfing through pages as part of an extended information-gathering process. We show that these three relationships can be mined using a combination of textual and link information and provide three scoring mechanisms that correspond to them: {\em SeekRel}, {\em FactRel} and {\em SurfRel}. These scoring mechanisms incorporate both textual and link information. We build a set of capacitated subnetworks, each corresponding to a particular keyword. Scores are computed by computing flows on these subnetworks. The capacities of the links are derived from the {\em hub} and {\em authority} values of the nodes they connect, following the work of Kleinberg (1998) on assigning authority to pages in hyperlinked environments. We evaluated our scoring mechanism by running experiments on four data sets taken from the Web. We present user evaluations of the relevance of the top results returned by our scoring mechanisms and compare those to the top results returned by Google's Similar Pages feature, and the {\em Companion} algorithm (Dean and Henzinger, 1999).},
  added-at = {2009-07-01T11:57:35.000+0200},
  address = {New York, NY, USA},
  author = {Bagchi, Amitabha and Lahoti, Garima},
  biburl = {http://www.bibsonomy.org/bibtex/254bbfae9ef1a8c308d0c0cd252a0a450/brusilovsky},
  booktitle = {HT '09: Proceedings of the Twentieth ACM Conference on Hypertext and Hypermedia},
  interhash = {ae8ad81a84f47764ef3868249dd92b80},
  intrahash = {54bbfae9ef1a8c308d0c0cd252a0a450},
  keywords = {authorities ht09 similarity},
  month = {July},
  paperid = {fp003},
  publisher = {ACM},
  session = {Full Paper},
  timestamp = {2009-07-01T11:57:35.000+0200},
  title = {Relating Web Pages to Enable Information-Gathering Tasks},
  year = 2009
}

Endnote record

%0 Conference Paper
%1 bagchi2009relating
%A Bagchi, Amitabha
%A Lahoti, Garima
%B HT '09: Proceedings of the Twentieth ACM Conference on Hypertext and Hypermedia
%C New York, NY, USA
%D 2009
%I ACM
%K 
%T Relating Web Pages to Enable Information-Gathering Tasks
%X We argue that relationships between Web pages are functions of the user's intent. We identify a class of Web tasks - information-gathering - that can be facilitated by providing links to pages related to the page the user is currently viewing. We define three kinds of intentional relationships that correspond to whether the user is a) seeking sources of information, b) reading pages which provide information, or c) surfing through pages as part of an extended information-gathering process. We show that these three relationships can be mined using a combination of textual and link information and provide three scoring mechanisms that correspond to them: {\em SeekRel}, {\em FactRel} and {\em SurfRel}. These scoring mechanisms incorporate both textual and link information. We build a set of capacitated subnetworks, each corresponding to a particular keyword. Scores are computed by computing flows on these subnetworks. The capacities of the links are derived from the {\em hub} and {\em authority} values of the nodes they connect, following the work of Kleinberg (1998) on assigning authority to pages in hyperlinked environments. We evaluated our scoring mechanism by running experiments on four data sets taken from the Web. We present user evaluations of the relevance of the top results returned by our scoring mechanisms and compare those to the top results returned by Google's Similar Pages feature, and the {\em Companion} algorithm (Dean and Henzinger, 1999).