NDLI: Tag-Weighted Dirichlet Allocation

Content Provider	IEEE Xplore Digital Library
Author	Shuangyin Li Guan Huang Ruiyang Tan Rong Pan
Copyright Year	2013
Description	Author affiliation: Sch. of Inf. Sci. & Technol., Sun Yat-sen Univ., Guangzhou, China (Shuangyin Li; Guan Huang; Ruiyang Tan; Rong Pan)
Abstract	In the past two decades, there has been a huge amount of document data with rich tag information during the evolution of the Internet, which can be called semi-structured data. These semi-structured data contain both unstructured features (e.g., plain text) and metadata, such as tags in html files or author and venue information in research articles. It's of great interest to model such kind of data. Most previous works focused on modeling the unstructured data. Some other methods have been proposed to model the unstructured data with specific tags. To build a general model for semi-structured documents remains an important problem in terms of both model fitness and efficiency. In this paper, we propose a novel method to model the tagged documents by a so-called Tag-Weighted Dirichlet Allocation (TWDA). TWDA is a framework that leverages both the tags and words in each document to infer the topic components for the documents. This allows not only to learn the document-topic and topic-word distributions, but also to infer the tag-topic distributions for text mining (e.g., classification, clustering, and recommendations). Moreover, TWDA can automatically infer the probabilistic weights of tags for each document, that can be used to predict the tags in one document. We present an efficient variational inference method with an EM algorithm for estimating the model parameters. The experimental results show the effectiveness, efficiency and robustness of our TWDA approach by comparing it with the state-of-the-art methods on four corpora in document modeling, tags prediction and text classification.
Sponsorship	Toshiba
Starting Page	438
Ending Page	447
File Size	267787
Page Count	10
File Format	PDF
ISBN	9780769551081
ISSN	15504786
DOI	10.1109/ICDM.2013.11
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-07
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data models Vectors Resource management Mathematical model Predictive models Probabilistic logic Analytical models variational inference Tag-Weighted Dirichlet allocation topic model
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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