Search (35 results, page 1 of 2)

  • × theme_ss:"Suchmaschinen"
  • × year_i:[2010 TO 2020}
  1. Ke, W.: Decentralized search and the clustering paradox in large scale information networks (2012) 0.02 
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    Abstract
    Amid the rapid growth of information today is the increasing challenge for people to navigate its magnitude. Dynamics and heterogeneity of large information spaces such as the Web raise important questions about information retrieval in these environments. Collection of all information in advance and centralization of IR operations are extremely difficult, if not impossible, because systems are dynamic and information is distributed. The chapter discusses some of the key issues facing classic information retrieval models and presents a decentralized, organic view of information systems pertaining to search in large scale networks. It focuses on the impact of network structure on search performance and discusses a phenomenon we refer to as the Clustering Paradox, in which the topology of interconnected systems imposes a scalability limit.
    Pages
    S.29-46
  2. Kaeser, E.: ¬Das postfaktische Zeitalter (2016) 0.01 
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    Content
    "Es gibt Daten, Informationen und Fakten. Wenn man mir eine Zahlenreihe vorsetzt, dann handelt es sich um Daten: unterscheidbare Einheiten, im Fachjargon: Items. Wenn man mir sagt, dass diese Items stündliche Temperaturangaben der Aare im Berner Marzilibad bedeuten, dann verfüge ich über Information - über interpretierte Daten. Wenn man mir sagt, dies seien die gemessenen Aaretemperaturen am 22. August 2016 im Marzili, dann ist das ein Faktum: empirisch geprüfte interpretierte Daten. Dieser Dreischritt - Unterscheiden, Interpretieren, Prüfen - bildet quasi das Bindemittel des Faktischen, «the matter of fact». Wir alle führen den Dreischritt ständig aus und gelangen so zu einem relativ verlässlichen Wissen und Urteilsvermögen betreffend die Dinge des Alltags. Aber wie schon die Kurzcharakterisierung durchblicken lässt, bilden Fakten nicht den Felsengrund der Realität. Sie sind kritikanfällig, sowohl von der Interpretation wie auch von der Prüfung her gesehen. Um bei unserem Beispiel zu bleiben: Es kann durchaus sein, dass man uns zwei unterschiedliche «faktische» Temperaturverläufe der Aare am 22. August 2016 vorsetzt.
    Date
    24. 8.2016 9:29:24
  3. Ozcan, R.; Altingovde, I.S.; Ulusoy, O.: Exploiting navigational queries for result presentation and caching in Web search engines (2011) 0.01 
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    Abstract
    Caching of query results is an important mechanism for efficiency and scalability of web search engines. Query results are cached and presented in terms of pages, which typically include 10 results each. In navigational queries, users seek a particular website, which would be typically listed at the top ranks (maybe, first or second) by the search engine, if found. For this type of query, caching and presenting results in the 10-per-page manner may waste cache space and network bandwidth. In this article, we propose nonuniform result page models with varying numbers of results for navigational queries. The experimental results show that our approach reduces the cache miss count by up to 9.17% (because of better utilization of cache space). Furthermore, bandwidth usage, which is measured in terms of number of snippets sent, is also reduced by 71% for navigational queries. This means a considerable reduction in the number of transmitted network packets, i.e., a crucial gain especially for mobile-search scenarios. A user study reveals that users easily adapt to the proposed result page model and that the efficiency gains observed in the experiments can be carried over to real-life situations.
  4. Shapira, B.; Zabar, B.: Personalized search : integrating collaboration and social networks (2011) 0.01 
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    Abstract
    Despite improvements in their capabilities, search engines still fail to provide users with only relevant results. One reason is that most search engines implement a "one size fits all" approach that ignores personal preferences when retrieving the results of a user's query. Recent studies (Smyth, 2010) have elaborated the importance of personalizing search results and have proposed integrating recommender system methods for enhancing results using contextual and extrinsic information that might indicate the user's actual needs. In this article, we review recommender system methods used for personalizing and improving search results and examine the effect of two such methods that are merged for this purpose. One method is based on collaborative users' knowledge; the second integrates information from the user's social network. We propose new methods for collaborative-and social-based search and demonstrate that each of these methods, when separately applied, produce more accurate search results than does a purely keyword-based search engine (referred to as "standard search engine"), where the social search engine is more accurate than is the collaborative one. However, separately applied, these methods do not produce a sufficient number of results (low coverage). Nevertheless, merging these methods with those implemented by standard search engines overcomes the low-coverage problem and produces personalized results for users that display significantly more accurate results while also providing sufficient coverage than do standard search engines. The improvement, however, is significant only for topics for which the diversity of terms used for queries among users is low.
  5. Gencosman, B.C.; Ozmutlu, H.C.; Ozmutlu, S.: Character n-gram application for automatic new topic identification (2014) 0.01 
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    Abstract
    The widespread availability of the Internet and the variety of Internet-based applications have resulted in a significant increase in the amount of web pages. Determining the behaviors of search engine users has become a critical step in enhancing search engine performance. Search engine user behaviors can be determined by content-based or content-ignorant algorithms. Although many content-ignorant studies have been performed to automatically identify new topics, previous results have demonstrated that spelling errors can cause significant errors in topic shift estimates. In this study, we focused on minimizing the number of wrong estimates that were based on spelling errors. We developed a new hybrid algorithm combining character n-gram and neural network methodologies, and compared the experimental results with results from previous studies. For the FAST and Excite datasets, the proposed algorithm improved topic shift estimates by 6.987% and 2.639%, respectively. Moreover, we analyzed the performance of the character n-gram method in different aspects including the comparison with Levenshtein edit-distance method. The experimental results demonstrated that the character n-gram method outperformed to the Levensthein edit distance method in terms of topic identification.
  6. Roy, R.S.; Agarwal, S.; Ganguly, N.; Choudhury, M.: Syntactic complexity of Web search queries through the lenses of language models, networks and users (2016) 0.01 
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    Abstract
    Across the world, millions of users interact with search engines every day to satisfy their information needs. As the Web grows bigger over time, such information needs, manifested through user search queries, also become more complex. However, there has been no systematic study that quantifies the structural complexity of Web search queries. In this research, we make an attempt towards understanding and characterizing the syntactic complexity of search queries using a multi-pronged approach. We use traditional statistical language modeling techniques to quantify and compare the perplexity of queries with natural language (NL). We then use complex network analysis for a comparative analysis of the topological properties of queries issued by real Web users and those generated by statistical models. Finally, we conduct experiments to study whether search engine users are able to identify real queries, when presented along with model-generated ones. The three complementary studies show that the syntactic structure of Web queries is more complex than what n-grams can capture, but simpler than NL. Queries, thus, seem to represent an intermediate stage between syntactic and non-syntactic communication.
  7. Peters, I.: Folksonomies und kollaborative Informationsdienste : eine Alternative zur Websuche? (2011) 0.01 
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    Pages
    S.29-53
  8. Jezior, T.: Adaption und Integration von Suchmaschinentechnologie in mor(!)dernen OPACs (2013) 0.01 
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    Date
    18.10.2015 10:29:56
  9. Lewandowski, D.: Query understanding (2011) 0.01 
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    Date
    18. 9.2018 18:22:18
  10. Bensman, S.J.: Eugene Garfield, Francis Narin, and PageRank : the theoretical bases of the Google search engine (2013) 0.01 
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    Date
    17.12.2013 11:02:22
  11. Tober, M.; Hennig, L.; Furch, D.: SEO Ranking-Faktoren und Rang-Korrelationen 2014 : Google Deutschland (2014) 0.01 
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    Date
    13. 9.2014 14:45:22
  12. Schaat, S.: Von der automatisierten Manipulation zur Manipulation der Automatisierung (2019) 0.01 
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    Date
    19. 2.2019 17:22:00
  13. Franke-Maier, M.; Rüter, C.: Discover Sacherschließung! : Was machen suchmaschinenbasierte Systeme mit unseren inhaltlichen Metadaten? (2015) 0.00 
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    Date
    2. 3.2015 10:29:44
  14. Lewandowski, D.: Perspektiven eines Open Web Index (2016) 0.00 
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    Date
    16. 5.2016 21:53:29
  15. Fluhr, C.: Crosslingual access to photo databases (2012) 0.00 
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    Date
    17. 4.2012 14:25:22
  16. Chen, L.-C.: Next generation search engine for the result clustering technology (2012) 0.00 
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    Date
    17. 4.2012 15:22:11
  17. Bouidghaghen, O.; Tamine, L.: Spatio-temporal based personalization for mobile search (2012) 0.00 
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    Date
    20. 4.2012 13:19:22
  18. Lewandowski, D.: ¬Die Macht der Suchmaschinen und ihr Einfluss auf unsere Entscheidungen (2014) 0.00 
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    Date
    22. 9.2014 18:54:11
  19. Huvila, I.: Affective capitalism of knowing and the society of search engine (2016) 0.00 
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