Search (3 results, page 1 of 1)

  • × language_ss:"e"
  • × author_ss:"Lewandowski, D."
  1. Lewandowski, D.; Sünkler, S.: What does Google recommend when you want to compare insurance offerings? (2019) 0.02 
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    Abstract
    Purpose The purpose of this paper is to describe a new method to improve the analysis of search engine results by considering the provider level as well as the domain level. This approach is tested by conducting a study using queries on the topic of insurance comparisons. Design/methodology/approach The authors conducted an empirical study that analyses the results of search queries aimed at comparing insurance companies. The authors used a self-developed software system that automatically queries commercial search engines and automatically extracts the content of the returned result pages for further data analysis. The data analysis was carried out using the KNIME Analytics Platform. Findings Google's top search results are served by only a few providers that frequently appear in these results. The authors show that some providers operate several domains on the same topic and that these domains appear for the same queries in the result lists. Research limitations/implications The authors demonstrate the feasibility of this approach and draw conclusions for further investigations from the empirical study. However, the study is a limited use case based on a limited number of search queries. Originality/value The proposed method allows large-scale analysis of the composition of the top results from commercial search engines. It allows using valid empirical data to determine what users actually see on the search engine result pages.
    Date
    20. 1.2015 18:30:22
  2. Lewandowski, D.: Evaluating the retrieval effectiveness of web search engines using a representative query sample (2015) 0.01 
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    Abstract
    Search engine retrieval effectiveness studies are usually small scale, using only limited query samples. Furthermore, queries are selected by the researchers. We address these issues by taking a random representative sample of 1,000 informational and 1,000 navigational queries from a major German search engine and comparing Google's and Bing's results based on this sample. Jurors were found through crowdsourcing, and data were collected using specialized software, the Relevance Assessment Tool (RAT). We found that although Google outperforms Bing in both query types, the difference in the performance for informational queries was rather low. However, for navigational queries, Google found the correct answer in 95.3% of cases, whereas Bing only found the correct answer 76.6% of the time. We conclude that search engine performance on navigational queries is of great importance, because users in this case can clearly identify queries that have returned correct results. So, performance on this query type may contribute to explaining user satisfaction with search engines.
  3. Lewandowski, D.; Spree, U.: Ranking of Wikipedia articles in search engines revisited : fair ranking for reasonable quality? (2011) 0.00 
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    Date
    30. 9.2012 19:27:22

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