Search (3 results, page 1 of 1)

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Abstract

Very good site that includes search basics, Boolean logic. Reviews all the popular search engines and includes Size, Currency, Search options, and Results

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Abstract

Due to the advances in information retrieval in the past decades, search engines have become extremely efficient at acquiring useful sources in response to a user's query. However, for more prolonged and complex information seeking tasks, these search engines are not as well suited. During complex information seeking tasks, various stages may occur, which imply varying support needs for users. However, the implications of theoretical information seeking models for concrete search user interfaces (SUI) design are unclear, both at the level of the individual features and of the whole interface. Guidelines and design patterns for concrete SUIs, on the other hand, provide recommendations for feature design, but these are separated from their role in the information seeking process. This chapter addresses the question of how to design SUIs with enhanced support for the macro-level process, first by reviewing previous research. Subsequently, we outline a framework for complex task support, which explicitly connects the temporal development of complex tasks with different levels of support by SUI features. This is followed by a discussion of concrete system examples which include elements of the three dimensions of our framework in an exploratory search and sensemaking context. Moreover, we discuss the connection of navigation with the search-oriented framework. In our final discussion and conclusion, we provide recommendations for designing more holistic SUIs which potentially evolve along with a user's information seeking process.

Source

Understanding and improving information search [Vgl. unter: https://www.researchgate.net/publication/341747751_Designing_Multistage_Search_Systems_to_Support_the_Information_Seeking_Process]

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Abstract

Finding information located somewhere on the WWW is an error-prone and frustrating task. The WebQuey system offers a powerful new method for searching the Web based on connectivity and content. We do this by examining links among the nodes returned in a keyword-based query. We then rank the nodes, giving the highest rank to the most highly connected nodes. By doing so, we are finding 'hot spots' on the Web that contain onformation germane to a user's query. WebQuery not only ranks and filters the results of a Web query, it also extends the result set beyond what the search engine retrieves, by finding 'interesting' sites that are hoghly connected to those sites returned by the original query. Even with WebQuery filtering and ranking query results, the result sets can be enourmous. So, wen need to visualize the returned information. We explore several techniques for visualizing this information - including cone trees, 2D graphs, 3D graphy, lists, and bullseyes - and discuss the criteria for using each of the techniques