Assessing the relationship between context, user preferences, and content in search behaviour
|Assessing the relationship between context, user preferences, and content in search behaviour|
|Author(s)||Knaeusl H., Ludwig B.|
|Published in||International Conference on Information and Knowledge Management, Proceedings|
|Keyword(s)||Electromyography, Eye tracking, Preference elicitation, Reading behaviour, Wikipedia (Extra: Context-Aware, Experimental studies, Eye-tracking, Human decision making, Information need, Information search, Personalized model, Preference elicitation, Reading behaviour, Recommendation techniques, Search tasks, Selection problems, Web servers, Web users, Wikipedia, Electromyography, Information science, Knowledge based systems, Knowledge management, Search engines, Websites)|
|Article||BASE, CiteSeerX, Google Scholar|
|Web||Ask, Bing, Google (PDF), Yahoo!|
|Download and mirrors|
|Local copy||Not available|
|Remote mirror(s)||Not available|
|Export and share|
|BibTeX, CSV, RDF, JSON|
|Browse properties · List of conference papers|
Assessing the relationship between context, user preferences, and content in search behaviour is a 2012 conference paper written in English by Knaeusl H., Ludwig B. and published in International Conference on Information and Knowledge Management, Proceedings.
Searching information by using search engines and browsers is a tedious task for users. Navigational and informational search tasks are complicated by the fact that web servers always provide complete web pages and do not tailor their content to the user's current information need. In this paper, we present a proposal for the application of contextaware recommendation techniques to simulate human decision making when selecting elements of content to be included in an answer to an information need. As a first step towards live generation of content, we present results on our experimental study to capture decision criteria for this selection problem that web users apply in choosing content. These preferences could then later be formalized in terms of a knowledge-based context-aware and personalized model for recommending content during information search. Copyright
- This section requires expansion. Please, help!
Probably, this publication is cited by others, but there are no articles available for them in WikiPapers.