Looking back: On relevance, probabilistic indexing and information retrieval
نویسنده
چکیده
Forty-eight years ago Maron and Kuhns published their paper, ‘‘On Relevance, Probabilistic Indexing and Information Retrieval” (1960). This was the first paper to present a probabilistic approach to information retrieval, and perhaps the first paper on ranked retrieval. Although it is one of the most widely cited papers in the field of information retrieval, many researchers today may not be familiar with its influence. This paper describes the Maron and Kuhns article and the influence that it has had on the field of information retrieval. 2007 Elsevier Ltd. All rights reserved. Keyword: Probabilistic information retrieval
منابع مشابه
Optimizing Document Indexing and Search Term Weighting Based on Probabilistic Models
We describe the application of probabilistic indexing and retrieval methods to the TREC material. For document indexing, we apply a description-oriented approach which uses relevance feedback information from previous queries run on the same collection. This method is also very exible w.r.t. the underlying document representation. In our experiments, we consider single words and phrases and use...
متن کاملA syntactically-based query reformulation technique for information retrieval
Whereas in language words of high frequency are generally associated with low content [Bookstein, A., & Swanson, D. (1974). Probabilistic models for automatic indexing. Journal of the American Society of Information Science, 25(5), 312–318; Damerau, F. J. (1965). An experiment in automatic indexing. American Documentation, 16, 283–289; Harter, S. P. (1974). A probabilistic approach to automatic...
متن کاملModels for retrieval with probabilistic indexing
in this article three retrieval models for probabilistic indexing are described along with evaluation results for each. First is the binary independence indexing @II) model, which is a generalized version of the Maron and Kuhns indexing model. In this model, the indexing weight of a descriptor in a document is an estimate of the probability of relevance of this document with respect to queries ...
متن کاملDocument Image Retrieval Based on Keyword Spotting Using Relevance Feedback
Keyword Spotting is a well-known method in document image retrieval. In this method, Search in document images is based on query word image. In this Paper, an approach for document image retrieval based on keyword spotting has been proposed. In proposed method, a framework using relevance feedback is presented. Relevance feedback, an interactive and efficient method is used in this paper to imp...
متن کاملProbabilistic Modeling of Distributed Information Retrieval
This paper describes a model for optimum information retrieval over a distributed document collection. The model stems from Robertson's Probability Ranking Principle: Having computed individual document rankings correlated to diierent subcollections, these local rankings are stepwise merged into a nal ranking list where the documents are ordered according to their probability of relevance. Here...
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:
- Inf. Process. Manage.
دوره 44 شماره
صفحات -
تاریخ انتشار 2008