Question classification is very important for question answering. This paper presents our research work on automatic question classification through machine learning approaches. W...
In this paper, we introduce the fractal summarization model based on the fractal theory. In fractal summarization, the important information is captured from the source text by ex...
One of the major problems in question answering (QA) is that the queries are either too brief or often do not contain most relevant terms in the target corpus. In order to overcom...
We present a non-traditional retrieval problem we call subtopic retrieval. The subtopic retrieval problem is concerned with finding documents that cover many different subtopics ...
ChengXiang Zhai, William W. Cohen, John D. Laffert...
Current Web search engines generally impose link analysis-based re-ranking on web-page retrieval. However, the same techniques, when applied directly to small web search such as i...
We propose a Bayesian extension to the ad-hoc Language Model. Many smoothed estimators used for the multinomial query model in ad-hoc Language Models (including Laplace and Bayes-...
Hugo Zaragoza, Djoerd Hiemstra, Michael E. Tipping
In this paper, we propose a novel document clustering method based on the non-negative factorization of the termdocument matrix of the given document corpus. In the latent semanti...
Most existing clustering algorithms cluster highly related data objects such as Web pages and Web users separately. The interrelation among different types of data objects is eith...
Use of semantic content is one of the major issues which needs to be addressed for improving image retrieval effectiveness. We present a new approach to classify images based on t...
We investigate the criteria used by online searchers when assessing the relevance of web pages to information-seeking tasks. Twenty four searchers were given three tasks each, and...