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Shankara B. Subramanya

dblp:26/2505 · DBLP profile ↗
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3ranked-venue papers
0as first author
0since 2021 · last 2010
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 3Artificial intelligence and machine learning · 1Software engineering, systems software and programming languages · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Data mining · 56% Web and social media mining · 44%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Web and social media mining › social media analysis
blog analysis
0.112009
Connecting Sparsely Distributed Similar Bloggers · ICDM 2009
Data mining › structured data mining
graph mining
0.112009
Connecting Sparsely Distributed Similar Bloggers · ICDM 2009
Data mining › structured data mining › graph mining
community detection
0.012009
Connecting Sparsely Distributed Similar Bloggers · ICDM 2009

Methods — techniques the papers use, named apart from their topics

contextual information · 0.1collective wisdom · 0.1
YearPublicationVenuePosition
2010 WisColl: Collective wisdom based blog clustering
Nitin Agarwal 0001, Magdiel Galan Oliveras, Huan Liu 0001, Shankara B. Subramanya
Inf. Sci.4
2009 Connecting Sparsely Distributed Similar Bloggers
abstract
The nature of the Blogosphere determines that the majority of bloggers are only connected with a small number of fellow bloggers, and similar bloggers can be largely disconnected from each other. Aggregating them allows for cost-effective personalized services, targeted marketing, and exploration of new business opportunities. As most bloggers have only a small number of adjacent bloggers, the problem of aggregating similar bloggers presents challenges that demand novel algorithms of connecting the non-adjacent due to the fragmented distributions of bloggers. In this work, we define the problem, delineate its challenges, and present an approach that uses innovative ways to employ contextual information and collective wisdom to aggregate similar bloggers. A real-world blog directory is used for experiments. We demonstrate the efficacy of our approach, report findings, and discuss related issues and future work.
Nitin Agarwal 0001, Huan Liu 0001, Shankara B. Subramanya, John J. Salerno, Philip S. Yu
ICDM3
2008 Clustering Blogs with Collective Wisdom
abstract
Blogosphere is expanding in an unprecedented speed. A better understanding of the blogosphere can greatly facilitate the development of the Social Web to serve the needs of users, service providers and advertisers. One important task in this process is clustering blog sites. Clustering blog sites presents new challenges. We propose to tap into collective wisdom in clustering blog sites, present statistical and visual results, report findings, and suggest future work extending to many real-world applications.
Nitin Agarwal 0001, Magdiel Galan Oliveras, Huan Liu 0001, Shankara B. Subramanya
ICWE4