Semantic Approach to Discover Topic over Mail Data

D.A. Kiran Kumar

Semantic Approach to Discover Topic over Mail Data

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D.A. Kiran Kumar

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§ Jawaharlal Nehru Technological University, Hyderabad

Semantic Approach to Discover Topic over Mail Data

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Abstract

Text sequences or Time stamped texts, are everpresent in real-world applications. Multiple text sequences are frequently connected to each other by distributing common topics. The correspondence between these sequences provides more significant and comprehensive clues for topic mining than those from every individual sequence. However, it is non retrieval to explore the equivalence with the existence of asynchronism among multiple sequences, i.e., documents from different sequences about the same topic may have different time stamps. In this paper, we properly addressed the problem and suggested a new algorithm based on the generative topic model. The proposed algorithm consists of two alternate steps: the first step retrieves common data from multiple sequences based on the arranged time stamps provided by the second step; the second step arranges the time stamps of the documents according to the time distribution of the topics found by the first step. We accomplish these two steps simultaneously and after number retrievals a monotonic convergence of our objective function can be extracted. The effectiveness and advantage of our approach were justified through extensive practical studies on two real data sets consisting of six research paper repositories and two news article feeds, respectively

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

D.A. Kumar. 2013. "Semantic Approach to Discover Topic over Mail Data". Global Journal of Computer Science and Technology GJCST-SPECIAL Volume 13 (GJCST Volume 13 Issue Special1).

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

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Submission ReceivedDecember 15, 2012
Peer Review Double Blind
Handling Editor
Accepted January 2, 2013
Published January 15, 2013

Version of record

v1.2

Issue date

August 25, 2013

Language

English

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Article Matrices

Total Score: 142

Country: India

Subject: Global Journal of Computer Science and Technology

Authors: D.A. Kiran Kumar, M. Saidi Reddy (PhD/Dr. count: 0)

View Count (all-time): 281

Total Views (Real + Logic): 1528

Total Downloads (simulated): 62

Publish Date: 2013 01, Tue

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Total Views: 1.5K

Total Downloads: 62

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