Description of an experimental on-line, minicomputer-based information retrieval system /

Thesis (M. S.)--University of Illinois at Urbana-Champaign.

Evaluation of selected features of the Eureka full-text information retrieval system /

Vita.

An experimental information retrieval system /

Bibliography: p. 114.

A thesaurus feature for the EUREKA information retrieval system /

Thesis (M. S.)--University of Illinois at Urbana-Champaign.

A unique word-scanning facility for the Eureka full-text information retrieval system /

Thesis (M.S.)--University of Illinois at Urbana-Champaign.

Users' guide to the Solid Waste Information Retrieval System thesaurus /

"Originally issued in 1973 as open-file report SW-104of."

Exploiting Learning Technologies for World Wide Web Agents

Postprint

Three dimensional visualization of the World Wide Web

Although large-scale public hypermedia structures such as the World Wide Web are popularly referred to as "cyberspace", the extent to which they constitute a space in the everyday sense of the word is questionable. This paper reviews recent work in the area of three dimensional (3D) visualization of the Web that has attempted to depict it in the form of a recognizable space; in other words, as a navigable landscape that may be visibly populated by its users. Our review begins by introducing a range of visualizations that address different aspects of using the Web. These include visualizations of Web structure, especially of links, that act as 3D maps; browsing history; searches; evolution of the Web; and the presence and activities of multiple users. We then summarize the different techniques that are employed by these visualizations. We conclude with a discussion of key challenges for the future.

La World Wide Web como herramienta eficiente de comunicación empresarial: análisis Web de la firma española de moda www.margalariz.es

Tesis inédita presentada en la Universidad Europea de Madrid. Facultad de Artes y Comunicación. Programa de Doctorado en Comunicación

Intelligent encoding of concepts in web development retrieval

The main aim of the proposed approach presented in this paper is to improve Web information retrieval effectiveness by overcoming the problems associated with a typical keyword matching retrieval system, through the use of concepts and an intelligent fusion of confidence values. By exploiting the conceptual hierarchy of the WordNet (G. Miller, 1995) knowledge base, we show how to effectively encode the conceptual information in a document using the semantic information implied by the words that appear within it. Rather than treating a word as a string made up of a sequence of characters, we consider a word to represent a concept.

Self-supervised information retrieval: a novel approach based on Deep Metric Learning and Neural Language Models

Most of the existing open-source search engines, utilize keyword or tf-idf based techniques to find relevant documents and web pages relative to an input query. Although these methods, with the help of a page rank or knowledge graphs, proved to be effective in some cases, they often fail to retrieve relevant instances for more complicated queries that would require a semantic understanding to be exploited. In this Thesis, a self-supervised information retrieval system based on transformers is employed to build a semantic search engine over the library of Gruppo Maggioli company. Semantic search or search with meaning can refer to an understanding of the query, instead of simply finding words matches and, in general, it represents knowledge in a way suitable for retrieval. We chose to investigate a new self-supervised strategy to handle the training of unlabeled data based on the creation of pairs of ’artificial’ queries and the respective positive passages. We claim that by removing the reliance on labeled data, we may use the large volume of unlabeled material on the web without being limited to languages or domains where labeled data is abundant.

English-Malayalam Cross-Lingual Information Retrieval – an Experience

This paper describes about an English-Malayalam Cross-Lingual Information Retrieval system. The system retrieves Malayalam documents in response to query given in English or Malayalam. Thus monolingual information retrieval is also supported in this system. Malayalam is one of the most prominent regional languages of Indian subcontinent. It is spoken by more than 37 million people and is the native language of Kerala state in India. Since we neither had any full-fledged online bilingual dictionary nor any parallel corpora to build the statistical lexicon, we used a bilingual dictionary developed in house for translation. Other language specific resources like Malayalam stemmer, Malayalam morphological root analyzer etc developed in house were used in this work