Statistical language models have recently been successfully applied to many information
retrieval problems. A great deal of recent work has shown that statistical language models …

Hierarchical modeling is a fundamental concept in Bayesian statistics. The basic idea is that
parameters are endowed with distributions which may themselves introduce new …

Information retrieval (IR) has changed considerably in recent years with the expansion of the
World Wide Web and the advent of modern and inexpensive graphical user interfaces and …

Language modeling approaches to information retrieval are attractive and promising
because they connect the problem of retrieval with that of language model estimation, which …

Language modeling approaches to information retrieval are attractive and promising
because they connect the problem of retrieval with that of language model estimation, which …

The language modeling approach to retrieval has been shown to perform well empirically.
One advantage of this new approach is its statistical foundations. However, feedback, as …

We present a framework for information retrieval that combines document models and query
models using a probabilistic ranking function based on Bayesian decision theory. The …

With the advent of the Web along with the unprecedented amount of information available in
electronic format, conceptual data analysis is more useful and practical than ever, because …

We present a new method for information retrieval using hidden Markov models (HMMs). We
develop a general framework for incorporating multiple word generation mechanisms within …

Because of the world wide web, information retrieval systems are now used by millions of
untrained users all over the world. The search engines that perform the information retrieval …