Text mining reading group

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(New page: <p><b>Date</b>: August 21, 2008</p><p> <b>Time </b>: 10.00 AM - 11.00 AM</p><p> <b>Location</b>: RISE Lab</p><p> <b>Speaker</b>: Kiran Kate - MTech Student</p><p> <b>Title</b>: On the ...)
 
 
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<p><b>Date</b>: August 21, 2008</p><p>
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This meeting is a forum to discuss the recent work in the text mining and social network analysis research. Students share interesting works they have come across.
<b>Time </b>:  10.00 AM - 11.00 AM</p><p>
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<b>Location</b>: RISE Lab</p><p>
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<b>Speaker</b>: Kiran Kate - MTech Student</p><p>
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'''Meetings in the Past:'''
<b>Title</b>: On the Structural Properties of Massive Telecom Call Graphs: Findings and Implications by Amit A. Nanavati, Siva Gurumurthy,Gautam Das, Dipanjan Chakraborty,Koustuv Dasgupta, Sougata Mukherjea and Anupam Joshi</p><p>
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<b>Abstract</b>: With ever growing competition in telecommunications markets,operators have to increasingly rely on business intelligence to offer the right incentives to their customers. Toward this end, existing approaches have almost solely focussed on the individual behaviour of customers. Call graphs, that is, graphs induced by people calling each other, can allow telecom operators to better understand the interaction behaviour of their customers, and potentially provide major insights for designing effective incentives.In this paper, we use the Call Detail Records of a mobile operator from four geographically disparate regions to construct call graphs, and analyse their structural properties.Our findings provide business insights and help devise strategies for Mobile Telecom operators. Another goal of this paper is to identify the shape of such graphs. In order to do so, we extend the well-known reachability analysis approach with some of our own techniques to reveal the shape of such massive graphs. Based on our analysis, we introduce the Treasure-Hunt model to describe the shape of mobile call graphs. The proposed techniques are general enough for analysing any large graph. Finally, how well the proposed model captures the shape of other mobile call graphs needs to be the subject of future studies.</p>
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Aug 21, 2008    [[On the Structural Properties of Massive Telecom Call Graphs: Findings and Implications]] - Kiran Kate, MTech Student<br>
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Sept 4, 2008    [[Social Ties and their Relevance to Churn in Mobile Telecom Networks]] - Kiran Kate, MTech Student<br>
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Oct 16, 2008    No Meeting. [[Identity and Search in social networks]] - Hemang Mandalia, MTech (CSE) student<br>
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Nov 6, 2008    Video Lecture from SIGKDD 2008 [http://videolectures.net/kdd08_seshadri_mcgbpl/ Mobile Call Graphs: Beyond Power-Law and Lognormal Distributions]<br>
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Nov 13, 2008    Lexical Chains for summarization - Abhishek (<i> Postponed to Nov 27th</i>)<br>
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Nov 20, 2008    [[Clustering Web Search Results]] - Manish <br>
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Nov 27, 2008    Lexical Chains for summarization [http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.36.4445] - Abhishek<br>
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Feb 19, 2008    Temporal indexing through lexical chains.[http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.54.1443] - Abhishek

Latest revision as of 15:54, 16 September 2009

This meeting is a forum to discuss the recent work in the text mining and social network analysis research. Students share interesting works they have come across.


Meetings in the Past:

Aug 21, 2008 On the Structural Properties of Massive Telecom Call Graphs: Findings and Implications - Kiran Kate, MTech Student
Sept 4, 2008 Social Ties and their Relevance to Churn in Mobile Telecom Networks - Kiran Kate, MTech Student
Oct 16, 2008 No Meeting. Identity and Search in social networks - Hemang Mandalia, MTech (CSE) student
Nov 6, 2008 Video Lecture from SIGKDD 2008 Mobile Call Graphs: Beyond Power-Law and Lognormal Distributions
Nov 13, 2008 Lexical Chains for summarization - Abhishek ( Postponed to Nov 27th)
Nov 20, 2008 Clustering Web Search Results - Manish
Nov 27, 2008 Lexical Chains for summarization [1] - Abhishek
Feb 19, 2008 Temporal indexing through lexical chains.[2] - Abhishek

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