S
Surya Ganesh
Researcher at International Institute of Information Technology, Hyderabad
Publications - 7
Citations - 148
Surya Ganesh is an academic researcher from International Institute of Information Technology, Hyderabad. The author has contributed to research in topics: Question answering & Conditional random field. The author has an hindex of 5, co-authored 7 publications receiving 146 citations.
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Journal Article
IIIT Hyderabad at TAC 2008
Vasudeva Varma,Prasad Pingali,Rahul Katragadda,Sai Krishna,Surya Ganesh,Kiran Sarvabhotla,Harish Garapati,Hareen Gopisetty,Vijay Bharath Reddy,B Kranthi Reddy,Praveen Bysani,Rohit G. Bharadwaj +11 more
TL;DR: The authors used a graph partition matching based approach to find opinionated sentences and also the polarity of the opinions to handle opinion expressed in the question, and for the squishy list questions, they leveraged on their existing Summarization engine and used a classification based approach.
Proceedings Article
Statistical Transliteration for Cross Langauge Information Retrieval using HMM alignment and CRF
TL;DR: The results show that the technique perfoms better than the existing transliteration system which uses HMM alignment and conditional probabilities derived from counting the alignments.
Proceedings ArticleDOI
A Language-Independent Transliteration Schema Using Character Aligned Models at NEWS 2009
TL;DR: A statistical transliteration technique that is language independent that uses statistical alignment models and Conditional Random Fields and has efficient training and decoding processes which is conditioned on both source and target languages and produces globally optimal solution.
Proceedings Article
Exploiting Structure and Content of Wikipedia for Query Expansion in the Context
Surya Ganesh,Vasudeva Varma +1 more
TL;DR: A novel query expansion method which aims to rank the answer containing passages better by using content and structured information of Wikipedia to generate a set of terms semantically related to the question.
Exploiting structure and content of Wikipedia for Query Expansion in the context of Question Answering
Surya Ganesh,Vasudeva Varma +1 more
TL;DR: In this paper, a query expansion method was proposed to rank the answer containing passages better, which uses content and structured information (link structure and category information) of Wikipedia to generate a set of terms semantically related to the question.