Discriminative graphical models for faculty homepage discovery

Faculty homepage discovery is an important step toward building an academic portal. Although the general homepage finding tasks have been well studied (e.g., TREC-2001 Web Track), faculty homepage discovery has its own special characteristics and not much focused research has been conducted for this task. In this paper, we view faculty homepage discovery as text categorization problems by utilizing Yahoo BOSS API to generate a small list of high-quality candidate homepages. Because the labels of these pages are not independent, standard text categorization methods such as logistic regression, which classify each page separately, are not well suited for this task. By defining homepage dependence graph, we propose a conditional undirected graphical model to make joint predictions by capturing the dependence of the decisions on all the candidate pages. Three cases of dependencies among faculty candidate homepages are considered for constructing the graphical model. Our model utilizes a discriminative approach so that any informative features can be used conveniently. Learning and inference can be done relatively efficiently for the joint prediction model because the homepage dependence graphs resulting from the three cases of dependencies are not densely connected. An extensive set of experiments have been conducted on two testbeds to show the effectiveness of the proposed discriminative graphical model.

[1]  Stephen E. Robertson,et al.  Effective site finding using link anchor information , 2001, SIGIR '01.

[2]  Ellen M. Voorhees,et al.  Overview of TREC 2001 , 2001, TREC.

[3]  Ben Taskar,et al.  Discriminative Probabilistic Models for Relational Data , 2002, UAI.

[4]  Raghu Ramakrishnan,et al.  Community Information Management , 2006, IEEE Data Eng. Bull..

[5]  Jie Tang,et al.  Social Network Extraction of Academic Researchers , 2007, Seventh IEEE International Conference on Data Mining (ICDM 2007).

[6]  Michael I. Jordan,et al.  Loopy Belief Propagation for Approximate Inference: An Empirical Study , 1999, UAI.

[7]  Oren Etzioni,et al.  Dynamic Reference Sifting: A Case Study in the Homepage Domain , 1997, Comput. Networks.

[8]  Ben Taskar,et al.  Probabilistic Entity-Relationship Models, PRMs, and Plate Models , 2007 .

[9]  Michael I. Jordan Learning in Graphical Models , 1999, NATO ASI Series.

[10]  Yiming Yang,et al.  A Comparative Study on Feature Selection in Text Categorization , 1997, ICML.

[11]  Ben Taskar,et al.  Introduction to statistical relational learning , 2007 .

[12]  W. Freeman,et al.  Generalized Belief Propagation , 2000, NIPS.

[13]  Andrew McCallum,et al.  Efficiently Inducing Features of Conditional Random Fields , 2002, UAI.

[14]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[15]  Jennifer Neville,et al.  Collective Classification with Relational Dependency Networks , 2003 .

[16]  Edward A. Fox,et al.  Machine Learning Approach for Homepage Finding Task , 2002, TREC.

[17]  David Hawking,et al.  Overview of the TREC-2001 Web track , 2002 .

[18]  James P. Callan,et al.  Combining document representations for known-item search , 2003, SIGIR.

[19]  Andrew McCallum,et al.  Extracting social networks and contact information from email and the Web , 2004, CEAS.

[20]  David Hawking,et al.  TREC10 Web and Interactive Tracks at CSIRO , 2001, TREC.

[21]  Fabrizio Sebastiani,et al.  Machine learning in automated text categorization , 2001, CSUR.

[22]  Yiming Yang,et al.  A re-examination of text categorization methods , 1999, SIGIR '99.

[23]  Djoerd Hiemstra,et al.  The Importance of Prior Probabilities for Entry Page Search , 2002, SIGIR '02.

[24]  Djoerd Hiemstra,et al.  Retrieving Web Pages Using Content, Links, URLs and Anchors , 2001, TREC.

[25]  Andrew McCallum,et al.  Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data , 2001, ICML.

[26]  Brian D. Davison Topical locality in the Web , 2000, SIGIR '00.

[27]  David Hawking,et al.  Query-independent evidence in home page finding , 2003, TOIS.