The librarianship and information science: coverage of Google Scholar, Citeseer and LISA

Jumei Zhang

    Research output: Book/ReportBookpeer-review


    Commercial abstracting and indexing (A&I) databases have been the dominant force for searching and indexing scholarly information and documents in the past few decades. However, aided by the latest search technologies, robotic search engines (especially Google Scholar) have rapidly become serious challengers in this area by providing similar, but free services to all Internet users. Due to their obvious advantages (such as high accessibility, simplicity), these search engines have been widely used by many users. However, these scholarly-oriented search engines have been the subjects of many critics due to their poor service qualities and other reasons.

    This dissertation reports a study to investigate and compare the coverage of Google Scholar, Citeseer in comparison with a traditional abstracting and indexing service (LISA) in library and information science. The research is motivated by an overview of the previous research, which found that there lacks systematic and comprehensive studies and comparisons in relation to the coverage of Google Scholar and conventional A&I databases for searching scholarly information or documents. Fifty queries (including 43 subject-based queries and 7 author-based queries) within the subject area were used to evaluate the coverage of the three investigated search engines/database under fifteen evaluation criteria, which can be broadly categorised into five coverage aspects: documents coverage, format, time span, language, and geographic coverage.

    The results indicate that generally Citeseer has the worst performance both for subject-based and author-based topics. However, it is quite difficult to separate the performance between Google Scholar and LISA, both of which have their advantages and disadvantages in terms of the five coverage aspects. From the query type perspective, the results show that both Google Scholar and LISA performed better for author-based queries than for subject-based queries. However, there are no definite preferences between author-based queries and subject-based queries for Citeseer. This may be ascribed to the fact that Citeseer does not have the specific functionality for author-based queries.

    Overall, it was found that no single search engine or database would cover all the relevant information. Choosing an appropriate search engine or database should consider different circumstances of searching topics and user demand scenarios. A combination of search engines and databases should be adopted to achieve comprehensive relevant information for a given topic.  
    Original languageEnglish
    Place of PublicationSaarbrücken
    PublisherLAP Lambert Academic Publishing
    Number of pages184
    ISBN (Print)9783838387116
    Publication statusPublished - 29 Jul 2010


    • Librarianship
    • Information science
    • Coverage
    • Google Scholar
    • Citeseer
    • LISA
    • Search engine
    • Databases


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