S
Srikanta Bedathur
Researcher at Indian Institute of Technology Delhi
Publications - 120
Citations - 1897
Srikanta Bedathur is an academic researcher from Indian Institute of Technology Delhi. The author has contributed to research in topics: Computer science & SPARQL. The author has an hindex of 21, co-authored 108 publications receiving 1680 citations. Previous affiliations of Srikanta Bedathur include IBM & Indraprastha Institute of Information Technology.
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Proceedings ArticleDOI
Towards time-aware link prediction in evolving social networks
TL;DR: In this paper, the authors investigate the value of incorporating the history information available on the interactions (or links) of the current social network state and show that time-stamps of past interactions significantly improve the prediction accuracy of new and recurrent links over rather sophisticated methods proposed recently.
Book ChapterDOI
A language modeling approach for temporal information needs
TL;DR: This work addresses information needs that have a temporal dimension conveyed by a temporal expression in the user’s query by integrating temporal expressions into a language modeling approach, thus making them first-class citizens of the retrieval model and considering their inherent uncertainty.
Proceedings ArticleDOI
Fast and accurate estimation of shortest paths in large graphs
TL;DR: This paper presents a scalable sketch-based index structure that not only supports estimation of node distances, but also computes corresponding shortest paths themselves, leading to near-exact shortest-path approximations in real world graphs.
Proceedings ArticleDOI
FERRARI: Flexible and efficient reachability range assignment for graph indexing
TL;DR: A scalable and highly efficient index structure for the reachability problem over graphs that imposes an explicit bound on the size of the index and flexibly assign approximate reachability ranges to nodes of the graph such that the number of index probes to answer a query is minimized.
Proceedings ArticleDOI
A time machine for text search
TL;DR: This work proposes an efficient solution for time-travel text search by extending the inverted file index to make it ready for temporal search, and introduces approximate temporal coalescing as a tunable method to reduce the index size without significantly affecting the quality of results.