Generating Query Suggestions for Cross-language and Cross-terminology Health Information Retrieval

• Type: Article in International Conference Proceedings Book
• Date: 2020

Authors

Santos, PM (Author) Other; Carla Teixeira Lopes (Author) FEUP

Conference proceedings International

Title: Advances in Information Retrieval - 42nd European Conference on IR Research, ECIR 2020, Lisbon, Portugal, April 14-17, 2020, Proceedings, Part II

Pages: 344-351

42nd European Conference on IR Research, ECIR 2020

14 April 2020 through 17 April 2020

Indexing

Scopus - 1 Citation

Other information

Authenticus ID: P-00S-1Z6

DOI: 10.1007/978-3-030-45442-5_43

Abstract (EN): Medico-scientific concepts are not easily understood by laypeople that frequently use lay synonyms. For this reason, strategies that help users formulate health queries are essential. Health Suggestions is an existing extension for Google Chrome that provides suggestions in lay and medico-scientific terminologies, both in English and Portuguese. This work proposes, evaluates, and compares further strategies for generating suggestions based on the initial consumer query, using multi-concept recognition and the Unified Medical Language System (UMLS). The evaluation was done with an English and a Portuguese test collection, considering as baseline the suggestions initially provided by Health Suggestions. Given the importance of understandability, we used measures that combine relevance and understandability, namely, uRBP and uRBPgr. Our best method merges the Consumer Health Vocabulary (CHV)-preferred expression for each concept identified in the initial query for lay suggestions and the UMLS-preferred expressions for medico-scientific suggestions. Multi-concept recognition was critical for this improvement. © Springer Nature Switzerland AG 2020.

Language: English

Type (Professor's evaluation): Scientific