Understanding Web Search Patterns Through Exploratory Search as a Knowledge-intensive Proces

  • Marcelo Tibau UNIRIO
  • Sean Wolfgand Matsui Siqueira UNIRIO
  • Bernardo Pereira Nunes ANU

Resumo


To better understand users’ intent, Web search engines need to transcend its information sorter utility and acquire a more relevant ability concerning semantics’ discernment. This master thesis presents the Exploratory Search KiP model, which helps clarify the reasons why a subject is searched and supports the visualization of decision criteria used for choosing a specific search result. It also introduces the ESKiP Taxonomy of Query States; a classification framework that helps to represent the structure and behavior of query reformulation in search systems. As a result, the artifacts allowed to identify Web search and query reformulation patterns. The Exploratory Search KiP model also aided to distinguish three main behaviors involved in exploratory searches: (1) The ability to increase the level of familiarity with the topic and content searched (topic familiarity); (2) The ability to control the search process itself; and (3) The ability to assess the retrieved information relevance. For further reading: [Dias 2019] at UNIRIO’s repository. A summary article from the complete work was submitted to an international Information System Journal and is currently under review
Palavras-chave: Web Search Patterns, Knowledge-intensive Process, users’ intent

Referências

Dias , M. T. d. V. (2019). Understanding web search patterns through exploratory search as a knowledge-intensive process. Master’s thesis, Dissertação (Mestrado) - UNIRIO.
Publicado
03/11/2020
Como Citar

Selecione um Formato
TIBAU, Marcelo; SIQUEIRA, Sean Wolfgand Matsui; NUNES, Bernardo Pereira. Understanding Web Search Patterns Through Exploratory Search as a Knowledge-intensive Proces. In: CONCURSO DE TESES E DISSERTAÇÕES EM SISTEMAS DE INFORMAÇÃO - SIMPÓSIO BRASILEIRO DE SISTEMAS DE INFORMAÇÃO (SBSI), 16. , 2020, Evento Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2020 . p. 92-92. DOI: https://doi.org/10.5753/sbsi.2020.13131.