Ranking Structured Documents Using Utility Theory in the Bayesian Network Retrieval Model
نویسندگان
چکیده
In this paper a new method based on Utility and Decision theory is presented to deal with structured documents. The aim of the application of these methodologies is to refine a first ranking of structural units, generated by means of an Information Retrieval Model based on Bayesian Networks. Units are newly arranged in the new ranking by combining their posterior probabilities, obtained in the first stage, with the expected utility of retrieving them. The experimental work has been developed using the Shakespeare structured collection and the results show an improvement of the effectiveness of this new approach.
منابع مشابه
Using Fuzzy LR Numbers in Bayesian Text Classifier for Classifying Persian Text Documents
Text Classification is an important research field in information retrieval and text mining. The main task in text classification is to assign text documents in predefined categories based on documents’ contents and labeled-training samples. Since word detection is a difficult and time consuming task in Persian language, Bayesian text classifier is an appropriate approach to deal with different...
متن کاملInvestigating the Impact of Authors’ Rank in Bibliographic Networks on Expertise Retrieval
Background and Aim: this research investigates the impact of authors’ rank in Bibliographic networks on document-centered model of Expertise Retrieval. Its purpose is to find out what kind of authors’ ranking in bibliographic networks can improve the performance of document-centered model. Methodology: Current research is an experimental one. To operationalize research goals, a new test colle...
متن کاملMultiple utility constrained multi-objective programs using Bayesian theory
A utility function is an important tool for representing a DM’s preference. We adjoin utility functions to multi-objective optimization problems. In current studies, usually one utility function is used for each objective function. Situations may arise for a goal to have multiple utility functions. Here, we consider a constrained multi-objective problem with each objective having multiple utili...
متن کاملUsing Fuzzy LR Numbers in Bayesian Text Classifier for Classifying Persian Text Documents
Text Classification is an important research field in information retrieval and text mining. The main task in text classification is to assign text documents in predefined categories based on documents’ contents and labeled-training samples. Since word detection is a difficult and time consuming task in Persian language, Bayesian text classifier is an appropriate approach to deal with different...
متن کاملRéseau bayésien pour un modèle de Recherche d'Information agrégée dans des documents structurés
In this paper, we are interested in aggregated search in structured XML documents. We present a model for the structured information retrieval, based on the Bayesian networks theory. Relations query-terms and terms-elements are modelled through probability measures. In this model, the user’s query starts a process of propagation to recover the relevant and noredundant elements. Thus, instead of...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2003