This paper presents a means of automatically deriving a hierarchical organization of concepts from a set of documents without use of training data or standard clustering technique...
The fast growth of multimedia information in image and video databases has triggered research on efficient retrieval methods. This paper deals with structural queries, a type of c...
We present a new method for information retrievalusing hidden Markov models (HMMs). We develop a general framework for incorporating multiple word generation mechanisms within the...
This paper claims that Belief Revision can be seen as a theoretical framework for document ranking in Extended Boolean Models. For a model of Information Retrieval based on propos...
There has been much recent interest in retrieval of time series data. Earlier work has used a fixed similarity metric (e.g., Euclidean distance) to determine the similarity betwee...
We present an approach to information retrieval based on context distance and morphology. Context distance is a measure we use to assess the closeness of word meanings. This conte...
We define the problem of decomposing human-written summary sentences and propose a novel Hidden Markov Model solution to the problem. Human summarizers often rely on cutting and ...
Probabilistic Latent Semantic Indexing is a novel approach to automated document indexing which is based on a statistical latent class model for factor analysis of count data. Fit...