Abstract
An evaluation of a large, operational full-text document-retrieval system (containing roughly 350,000 pages of text) shows the system to be retrieving less than 20 percent of the documents relevant to a particular search. The findings are discussed in terms of the theory and practice of full-text document retrieval.
Keywords
Affiliated Institutions
Related Publications
Using Linear Algebra for Intelligent Information Retrieval
Currently, most approaches to retrieving textual materials from scientific databases depend on a lexical match between words in users’ requests and those in or assigned to docum...
Introduction to Information Retrieval
Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering f...
Item-based top-<i>N</i>recommendation algorithms
The explosive growth of the world-wide-web and the emergence of e-commerce has led to the development of recommender systems ---a personalized information filtering technology u...
Incorporating contextual information in recommender systems using a multidimensional approach
The article presents a multidimensional (MD) approach to recommender systems that can provide recommendations based on additional contextual information besides the typical info...
Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions
This paper presents an overview of the field of recommender systems and describes the current generation of recommendation methods that are usually classified into the following...
Publication Info
- Year
- 1985
- Type
- article
- Volume
- 28
- Issue
- 3
- Pages
- 289-299
- Citations
- 663
- Access
- Closed
External Links
Social Impact
Social media, news, blog, policy document mentions
Citation Metrics
Cite This
Identifiers
- DOI
- 10.1145/3166.3197