Using proximity and tag weights for focused retrieval in structured documents

Abstract

Focused information retrieval is concerned with the retrieval of small units of information. In this context, the structure of the documents as well as the proximity among query terms have been found useful for improving retrieval effectiveness. In this article, we propose an approach combining the proximity of the terms and the tags which mark these terms. Our approach is based on a Fetch and Browse method where the fetch step is performed with BM25 and the browse step with a structure enhanced proximity model. In this way, the ranking of a document depends not only upon the existence of the query terms within the document but also upon the tags which mark these terms. Thus, the document tends to be highly relevant when query terms are close together and are emphasized by tags. The evaluation of this model on a large XML structured collection provided by the INEX 2010 XML IR evaluation campaign shows that the use of term proximity and structure improves the retrieval effectiveness of BM25 in the context of focused information retrieval.

The Application of Artificial Intelligence Technologies as a Substitute for Reading and to Support and Enhance the Authoring of Scientific Review Articles

“…For example, the MeSH catalog of the year 2017 [100] provides approximately 5000 different terms alone for ''cancer'' (or neoplasms, respectively). However, we managed to map the complete term set of sector C (diseases) of the MeSH thesaurus of 2015 into input queries to search for relevant articles -in addition, we applied a proximity operator and algorithm framework [101] to identify diseases where the sequence of words may vary (e.g., ''connective tissue neoplasms'' and ''neoplasms of the connected tissue'') or where the medical term has been intercepted by other terms (''bacterial infections'' and ''bacterial skin infections''). The search for articles was limited to both the type of publication of ''Journal Article'' and a selection of 10 general highly ranked (H-Index) medical journals that have exclusively been dedicated to major medical research events [72].…”