-
Lewandowski, D.; Sünkler, S.: What does Google recommend when you want to compare insurance offerings? (2019)
0.03
0.028261498 = product of:
0.08478449 = sum of:
0.08478449 = sum of:
0.05284806 = weight(_text_:methodology in 5288) [ClassicSimilarity], result of:
0.05284806 = score(doc=5288,freq=2.0), product of:
0.21236731 = queryWeight, product of:
4.504705 = idf(docFreq=1328, maxDocs=44218)
0.047143444 = queryNorm
0.24885213 = fieldWeight in 5288, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.504705 = idf(docFreq=1328, maxDocs=44218)
0.0390625 = fieldNorm(doc=5288)
0.03193643 = weight(_text_:22 in 5288) [ClassicSimilarity], result of:
0.03193643 = score(doc=5288,freq=2.0), product of:
0.16508831 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.047143444 = queryNorm
0.19345059 = fieldWeight in 5288, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0390625 = fieldNorm(doc=5288)
0.33333334 = coord(1/3)
- 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
-
Lewandowski, D.; Mayr, P.: Exploring the academic invisible Web (2006)
0.01
0.00880801 = product of:
0.02642403 = sum of:
0.02642403 = product of:
0.05284806 = sum of:
0.05284806 = weight(_text_:methodology in 3752) [ClassicSimilarity], result of:
0.05284806 = score(doc=3752,freq=2.0), product of:
0.21236731 = queryWeight, product of:
4.504705 = idf(docFreq=1328, maxDocs=44218)
0.047143444 = queryNorm
0.24885213 = fieldWeight in 3752, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.504705 = idf(docFreq=1328, maxDocs=44218)
0.0390625 = fieldNorm(doc=3752)
0.5 = coord(1/2)
0.33333334 = coord(1/3)
- Abstract
- Purpose: To provide a critical review of Bergman's 2001 study on the Deep Web. In addition, we bring a new concept into the discussion, the Academic Invisible Web (AIW). We define the Academic Invisible Web as consisting of all databases and collections relevant to academia but not searchable by the general-purpose internet search engines. Indexing this part of the Invisible Web is central to scien-tific search engines. We provide an overview of approaches followed thus far. Design/methodology/approach: Discussion of measures and calculations, estima-tion based on informetric laws. Literature review on approaches for uncovering information from the Invisible Web. Findings: Bergman's size estimate of the Invisible Web is highly questionable. We demonstrate some major errors in the conceptual design of the Bergman paper. A new (raw) size estimate is given. Research limitations/implications: The precision of our estimate is limited due to a small sample size and lack of reliable data. Practical implications: We can show that no single library alone will be able to index the Academic Invisible Web. We suggest collaboration to accomplish this task. Originality/value: Provides library managers and those interested in developing academic search engines with data on the size and attributes of the Academic In-visible Web.
-
Lewandowski, D.: ¬The retrieval effectiveness of web search engines : considering results descriptions (2008)
0.01
0.00880801 = product of:
0.02642403 = sum of:
0.02642403 = product of:
0.05284806 = sum of:
0.05284806 = weight(_text_:methodology in 2345) [ClassicSimilarity], result of:
0.05284806 = score(doc=2345,freq=2.0), product of:
0.21236731 = queryWeight, product of:
4.504705 = idf(docFreq=1328, maxDocs=44218)
0.047143444 = queryNorm
0.24885213 = fieldWeight in 2345, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.504705 = idf(docFreq=1328, maxDocs=44218)
0.0390625 = fieldNorm(doc=2345)
0.5 = coord(1/2)
0.33333334 = coord(1/3)
- Abstract
- Purpose - The purpose of this paper is to compare five major web search engines (Google, Yahoo, MSN, Ask.com, and Seekport) for their retrieval effectiveness, taking into account not only the results, but also the results descriptions. Design/methodology/approach - The study uses real-life queries. Results are made anonymous and are randomized. Results are judged by the persons posing the original queries. Findings - The two major search engines, Google and Yahoo, perform best, and there are no significant differences between them. Google delivers significantly more relevant result descriptions than any other search engine. This could be one reason for users perceiving this engine as superior. Research limitations/implications - The study is based on a user model where the user takes into account a certain amount of results rather systematically. This may not be the case in real life. Practical implications - The paper implies that search engines should focus on relevant descriptions. Searchers are advised to use other search engines in addition to Google. Originality/value - This is the first major study comparing results and descriptions systematically and proposes new retrieval measures to take into account results descriptions.
-
Lewandowski, D.; Mayr, P.: Exploring the academic invisible Web (2006)
0.01
0.00880801 = product of:
0.02642403 = sum of:
0.02642403 = product of:
0.05284806 = sum of:
0.05284806 = weight(_text_:methodology in 2580) [ClassicSimilarity], result of:
0.05284806 = score(doc=2580,freq=2.0), product of:
0.21236731 = queryWeight, product of:
4.504705 = idf(docFreq=1328, maxDocs=44218)
0.047143444 = queryNorm
0.24885213 = fieldWeight in 2580, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.504705 = idf(docFreq=1328, maxDocs=44218)
0.0390625 = fieldNorm(doc=2580)
0.5 = coord(1/2)
0.33333334 = coord(1/3)
- Abstract
- Purpose: To provide a critical review of Bergman's 2001 study on the deep web. In addition, we bring a new concept into the discussion, the academic invisible web (AIW). We define the academic invisible web as consisting of all databases and collections relevant to academia but not searchable by the general-purpose internet search engines. Indexing this part of the invisible web is central to scientific search engines. We provide an overview of approaches followed thus far. Design/methodology/approach: Discussion of measures and calculations, estimation based on informetric laws. Literature review on approaches for uncovering information from the invisible web. Findings: Bergman's size estimate of the invisible web is highly questionable. We demonstrate some major errors in the conceptual design of the Bergman paper. A new (raw) size estimate is given. Research limitations/implications: The precision of our estimate is limited due to a small sample size and lack of reliable data. Practical implications: We can show that no single library alone will be able to index the academic invisible web. We suggest collaboration to accomplish this task. Originality/value: Provides library managers and those interested in developing academic search engines with data on the size and attributes of the academic invisible web.
-
Lewandowski, D.: ¬The retrieval effectiveness of search engines on navigational queries (2011)
0.01
0.00880801 = product of:
0.02642403 = sum of:
0.02642403 = product of:
0.05284806 = sum of:
0.05284806 = weight(_text_:methodology in 4537) [ClassicSimilarity], result of:
0.05284806 = score(doc=4537,freq=2.0), product of:
0.21236731 = queryWeight, product of:
4.504705 = idf(docFreq=1328, maxDocs=44218)
0.047143444 = queryNorm
0.24885213 = fieldWeight in 4537, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.504705 = idf(docFreq=1328, maxDocs=44218)
0.0390625 = fieldNorm(doc=4537)
0.5 = coord(1/2)
0.33333334 = coord(1/3)
- Abstract
- Purpose - The purpose of this paper is to test major web search engines on their performance on navigational queries, i.e. searches for homepages. Design/methodology/approach - In total, 100 user queries are posed to six search engines (Google, Yahoo!, MSN, Ask, Seekport, and Exalead). Users described the desired pages, and the results position of these was recorded. Measured success and mean reciprocal rank are calculated. Findings - The performance of the major search engines Google, Yahoo!, and MSN was found to be the best, with around 90 per cent of queries answered correctly. Ask and Exalead performed worse but received good scores as well. Research limitations/implications - All queries were in German, and the German-language interfaces of the search engines were used. Therefore, the results are only valid for German queries. Practical implications - When designing a search engine to compete with the major search engines, care should be taken on the performance on navigational queries. Users can be influenced easily in their quality ratings of search engines based on this performance. Originality/value - This study systematically compares the major search engines on navigational queries and compares the findings with studies on the retrieval effectiveness of the engines on informational queries.
-
Behnert, C.; Lewandowski, D.: ¬A framework for designing retrieval effectiveness studies of library information systems using human relevance assessments (2017)
0.01
0.00880801 = product of:
0.02642403 = sum of:
0.02642403 = product of:
0.05284806 = sum of:
0.05284806 = weight(_text_:methodology in 3700) [ClassicSimilarity], result of:
0.05284806 = score(doc=3700,freq=2.0), product of:
0.21236731 = queryWeight, product of:
4.504705 = idf(docFreq=1328, maxDocs=44218)
0.047143444 = queryNorm
0.24885213 = fieldWeight in 3700, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.504705 = idf(docFreq=1328, maxDocs=44218)
0.0390625 = fieldNorm(doc=3700)
0.5 = coord(1/2)
0.33333334 = coord(1/3)
- Abstract
- Purpose This paper demonstrates how to apply traditional information retrieval evaluation methods based on standards from the Text REtrieval Conference (TREC) and web search evaluation to all types of modern library information systems including online public access catalogs, discovery systems, and digital libraries that provide web search features to gather information from heterogeneous sources. Design/methodology/approach We apply conventional procedures from information retrieval evaluation to the library information system context considering the specific characteristics of modern library materials. Findings We introduce a framework consisting of five parts: (1) search queries, (2) search results, (3) assessors, (4) testing, and (5) data analysis. We show how to deal with comparability problems resulting from diverse document types, e.g., electronic articles vs. printed monographs and what issues need to be considered for retrieval tests in the library context. Practical implications The framework can be used as a guideline for conducting retrieval effectiveness studies in the library context. Originality/value Although a considerable amount of research has been done on information retrieval evaluation, and standards for conducting retrieval effectiveness studies do exist, to our knowledge this is the first attempt to provide a systematic framework for evaluating the retrieval effectiveness of twenty-first-century library information systems. We demonstrate which issues must be considered and what decisions must be made by researchers prior to a retrieval test.
-
Lewandowski, D.: Alles nur noch Google? : Entwicklungen im Bereich der WWW-Suchmaschinen (2002)
0.01
0.0085163815 = product of:
0.025549144 = sum of:
0.025549144 = product of:
0.051098287 = sum of:
0.051098287 = weight(_text_:22 in 997) [ClassicSimilarity], result of:
0.051098287 = score(doc=997,freq=2.0), product of:
0.16508831 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.047143444 = queryNorm
0.30952093 = fieldWeight in 997, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0625 = fieldNorm(doc=997)
0.5 = coord(1/2)
0.33333334 = coord(1/3)
- Date
- 29. 9.2002 18:49:22
-
Lewandowski, D.: Abfragesprachen und erweiterte Funktionen von WWW-Suchmaschinen (2004)
0.01
0.0085163815 = product of:
0.025549144 = sum of:
0.025549144 = product of:
0.051098287 = sum of:
0.051098287 = weight(_text_:22 in 2314) [ClassicSimilarity], result of:
0.051098287 = score(doc=2314,freq=2.0), product of:
0.16508831 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.047143444 = queryNorm
0.30952093 = fieldWeight in 2314, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0625 = fieldNorm(doc=2314)
0.5 = coord(1/2)
0.33333334 = coord(1/3)
- Date
- 28.11.2004 13:11:22
-
Lewandowski, D.: Query understanding (2011)
0.01
0.0085163815 = product of:
0.025549144 = sum of:
0.025549144 = product of:
0.051098287 = sum of:
0.051098287 = weight(_text_:22 in 344) [ClassicSimilarity], result of:
0.051098287 = score(doc=344,freq=2.0), product of:
0.16508831 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.047143444 = queryNorm
0.30952093 = fieldWeight in 344, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0625 = fieldNorm(doc=344)
0.5 = coord(1/2)
0.33333334 = coord(1/3)
- Date
- 18. 9.2018 18:22:18
-
Lewandowski, D.: ¬Die Macht der Suchmaschinen und ihr Einfluss auf unsere Entscheidungen (2014)
0.01
0.006387286 = product of:
0.019161858 = sum of:
0.019161858 = product of:
0.038323715 = sum of:
0.038323715 = weight(_text_:22 in 1491) [ClassicSimilarity], result of:
0.038323715 = score(doc=1491,freq=2.0), product of:
0.16508831 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.047143444 = queryNorm
0.23214069 = fieldWeight in 1491, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.046875 = fieldNorm(doc=1491)
0.5 = coord(1/2)
0.33333334 = coord(1/3)
- Date
- 22. 9.2014 18:54:11
-
Lewandowski, D.; Spree, U.: Ranking of Wikipedia articles in search engines revisited : fair ranking for reasonable quality? (2011)
0.01
0.0053227386 = product of:
0.015968215 = sum of:
0.015968215 = product of:
0.03193643 = sum of:
0.03193643 = weight(_text_:22 in 444) [ClassicSimilarity], result of:
0.03193643 = score(doc=444,freq=2.0), product of:
0.16508831 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.047143444 = queryNorm
0.19345059 = fieldWeight in 444, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0390625 = fieldNorm(doc=444)
0.5 = coord(1/2)
0.33333334 = coord(1/3)
- Date
- 30. 9.2012 19:27:22
