Pattan, Sachin (2015)
Distributed Search Intention Analysis for User-Centered Visualizations.
Technische Universität Darmstadt
Masterarbeit, Bibliographie
Kurzbeschreibung (Abstract)
In recent years, Web Search Engines (WSEs) are the most used Information Retrieval systems around the world. As the information available increases explosively, it becomes more difficult to fetch the information meeting the preferences. This calls for a deep study of knowledge about the users' preknowledge and intentions and hence is a critical area of research in many organizations. There are many existing implementations of search intention analysis in some famous search engines such as Google, Bing etc. There are also several researches which propose few approaches for search intention analysis. Still there is a lack of techniques for intention mining in the field of semantic visualizations as they are designed to provide the visual adaptations especially for Exploratory queries. Hence, it is critical to identify the exploratory and targeted search queries. Also, the advancements in the technologies of distributed software systems make them to be applicable in all the systems which need to do some sort of distribution of load. The search intention analysis requires the distribution of load to do parallel processing of intention mining. In this thesis, a new approach for classifying the search intention of users' in a distributed set up is described along with a deep study on existing approaches with their comparison. The approach uses the efficient parameters: word frequency, query length and entity matching for differentiating the user query into exploratory, targeted and analysis search queries. As the approach focuses mainly on frequency analysis of the words, the same is done with the help of many sources of information such as Wortschatz frequency service by university of Leipzig and the Microsoft Ngram service. The model is evaluated with the help of a survey tool and few Machine Learning techniques. The survey was conducted with more than hundred users and on evaluating the model with the collected data, the results look satisfactory.
| Typ des Eintrags: | Masterarbeit |
|---|---|
| Erschienen: | 2015 |
| Autor(en): | Pattan, Sachin |
| Art des Eintrags: | Bibliographie |
| Titel: | Distributed Search Intention Analysis for User-Centered Visualizations |
| Sprache: | Englisch |
| Publikationsjahr: | 2015 |
| Kurzbeschreibung (Abstract): | In recent years, Web Search Engines (WSEs) are the most used Information Retrieval systems around the world. As the information available increases explosively, it becomes more difficult to fetch the information meeting the preferences. This calls for a deep study of knowledge about the users' preknowledge and intentions and hence is a critical area of research in many organizations. There are many existing implementations of search intention analysis in some famous search engines such as Google, Bing etc. There are also several researches which propose few approaches for search intention analysis. Still there is a lack of techniques for intention mining in the field of semantic visualizations as they are designed to provide the visual adaptations especially for Exploratory queries. Hence, it is critical to identify the exploratory and targeted search queries. Also, the advancements in the technologies of distributed software systems make them to be applicable in all the systems which need to do some sort of distribution of load. The search intention analysis requires the distribution of load to do parallel processing of intention mining. In this thesis, a new approach for classifying the search intention of users' in a distributed set up is described along with a deep study on existing approaches with their comparison. The approach uses the efficient parameters: word frequency, query length and entity matching for differentiating the user query into exploratory, targeted and analysis search queries. As the approach focuses mainly on frequency analysis of the words, the same is done with the help of many sources of information such as Wortschatz frequency service by university of Leipzig and the Microsoft Ngram service. The model is evaluated with the help of a survey tool and few Machine Learning techniques. The survey was conducted with more than hundred users and on evaluating the model with the collected data, the results look satisfactory. |
| Freie Schlagworte: | Business Field: Visual decision support, Research Area: Human computer interaction (HCI), Semantics visualization, Semantic web, Adaptive visualization, Exploratory search, User-centered design, User-centered interaction, Human-centered computing, Human-computer interaction (HCI), Adaptive user interfaces, Adaption support, Adaptive control |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme |
| Hinterlegungsdatum: | 10 Mai 2019 05:16 |
| Letzte Änderung: | 10 Mai 2019 05:16 |
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