Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.Includes bibliographical references (leaves 125-128).Traditionally, information retrieval systems aim to maximize the number of relevant documents returned to a user within some window of the top. For that goal, the Probability Ranking Principle, which ranks documents in decreasing order of probability of relevance, is provably optimal. However, there are many scenarios in which that ranking does not optimize for the user's information need. One example is when the user would be satisfied with some limited number of relevant documents, rather than needing all relevant documents. We show that in such a scenario, an attempt to retu...
Building on previous work in the field of language modeling information retrieval (IR), this paper p...
We apply a well-known Bayesian probabilistic model to textual information retrieval: the classificat...
The paper combines a comprehensive account of a probabilistic model of retrieval with new systematic...
This thesis examined two research projects: probabilistic information retrieval modeling and third-o...
We consider the problem of optimally allocating a limited budget to acquire relevance judgments when...
We consider the problem of optimally allocating a limited budget to acquire relevance judgments when...
A solid research path towards new information retrieval models is to further develop the theory behi...
An algorithm is described for ordering by probability of relevance overlapping document subsets from...
PhDRetrieval models are the core components of information retrieval systems, which guide the docume...
We consider the problem of optimally allocating a limited budget to acquire relevance judgments when...
Over the years a number of models have been introduced as solutions to the central IR problem of ran...
In this thesis, I propose the relative term frequency to be integrated into traditional probabilisti...
Empirical studies of information retrieval methods show that good retrieval performance is closely r...
This paper presents a new probabilistic model of information retrieval. The most important modeling ...
Relevance is an essential concept in information retrieval (IR) and relevance estimation is a fundam...
Building on previous work in the field of language modeling information retrieval (IR), this paper p...
We apply a well-known Bayesian probabilistic model to textual information retrieval: the classificat...
The paper combines a comprehensive account of a probabilistic model of retrieval with new systematic...
This thesis examined two research projects: probabilistic information retrieval modeling and third-o...
We consider the problem of optimally allocating a limited budget to acquire relevance judgments when...
We consider the problem of optimally allocating a limited budget to acquire relevance judgments when...
A solid research path towards new information retrieval models is to further develop the theory behi...
An algorithm is described for ordering by probability of relevance overlapping document subsets from...
PhDRetrieval models are the core components of information retrieval systems, which guide the docume...
We consider the problem of optimally allocating a limited budget to acquire relevance judgments when...
Over the years a number of models have been introduced as solutions to the central IR problem of ran...
In this thesis, I propose the relative term frequency to be integrated into traditional probabilisti...
Empirical studies of information retrieval methods show that good retrieval performance is closely r...
This paper presents a new probabilistic model of information retrieval. The most important modeling ...
Relevance is an essential concept in information retrieval (IR) and relevance estimation is a fundam...
Building on previous work in the field of language modeling information retrieval (IR), this paper p...
We apply a well-known Bayesian probabilistic model to textual information retrieval: the classificat...
The paper combines a comprehensive account of a probabilistic model of retrieval with new systematic...