Raman Chandrasekar

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Lottg alld eolni)licated seltteltces prov(: to b(: a. stumbling block for current systems relying on N[, input. These systenls s tand to gaill frolil ntethods that syntacti<:aHy simplily su<:h sentences. ']b simplify a sen= tence, we nee<t an idea of tit(." structure of the sentence, to identify the <:omponents to be separated out. Obviously a parser couhl(More)
Long and complicated sentences pose various problems to many state-of-the-art natural language technologies. We have been exploring methods to automatically transform such sentences as to make them simpler. These methods involve the use of a rule-based system, driven by the syntax of the text in the domain of interest. Hand-crafting rules for every domain(More)
We describe an empirical evaluation of the utility of thumbnail previews in web search results. Results pages were constructed to show text-only summaries, thumbnail previews only, or the combination of text summaries and thumbnail previews. We found that in the combination case, users were able to make more accurate decisions about the potential relevance(More)
Work on evaluating and improving the relevance of web search engines typically use human relevance judgments or clickthrough data. Both these methods look at the problem of learning the mapping from queries to web pages. In this paper, we identify some issues with this approach, and suggest an alternative approach, namely, learning a mapping from web pages(More)
In this paper we describe a system called Glean which is predicated on the idea that any coher ent text contains signi cant latent information such as syntactic structure and patterns of lan guage use which can be used to enhance the per formance of Information Retrieval systems We propose an approach to information retrieval that makes use of syntactic(More)
The syntactic information latent in any coherent text can be exploited to overcome some inadequacies of keyword-based retrieval and make information retrieval more e ective. We have earlier quantitatively demonstrated how syntactic information is useful in ltering out irrelevant documents. We have implemented a system which exploits a rich syntactic(More)
Scoring the performance of a system is an extremely important aspect of coreference algorithm performance. The score for a particular run is the single strongest measure of how well the system is performing and it can strongly determine directions for further improvements. In this paper, we present several di erent scoring algorithms and detail their(More)
Any coherent text contains significant latent information, such as syntactic structure and patterns of language use. This information can be exploited to overcome the inadequacies of keyword-based retrieval and make information retrieval more efficient. In this paper, we demonstrate quantitatively how syntactic information is useful in filtering out(More)