Data Set Used
Previous research on cluster-based retrieval has been inconclusive as to whether it does bring improved retrieval effectiveness over document-based retrieval. Recent developments in the language modeling approach to IR have motivated us to re-examine this problem within this new retrieval framework. We propose two new models for cluster-based retrieval and… (More)
Previous research has shown that passage-level evidence can bring added benefits to document retrieval when documents are long or span different subject areas. Recent developments in language modeling approach to IR provided a new effective alternative to traditional retrieval models. These two streams of research motivate us to examine the use of passages… (More)
We report on our ongoing study of using the genre of Web pages to facilitate information exploration. By genre, we mean socially recognized regularities of form and purpose in documents (e.g., a letter, a memo, a research paper). Our study had three phases. First, through a user study, we identified genres which most/least frequently meet searchers'… (More)
Software – User profiles and alert services.
Cluster retrieval assumes that the probability of relevance of a document should depend on the relevance of other similar documents to the same query. The goal is to find the best group of documents. Many studies have examined the effectiveness of this approach, by employing different retrieval methods or clustering algorithms, but few have investigated… (More)
This paper describes a question answering system that automatically finds answers to questions in a large collection of documents. The prototype CNLP question answering system was developed for participation in the TREC-9 question answering track. The system uses a two-stage retrieval approach to answer finding based on keyword and named entity matching.… (More)
—This paper proposes a new clustering algorithm based on ant colony to solve the unsupervised clustering problem. Ant colony optimization (ACO) is a population-based meta-heuristic that can be used to find approximate solutions to difficult combinatorial optimization problems. Clustering Analysis, which is an important method in data mining, classifies a… (More)