Using terminological feedback for web search refinement: a log-based study
By Peter G. Anick. Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2003
334 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Information Systems
View Paper: https://www.semanticscholar.org/paper/3d9bd77ec8e09f3987debbaa0df19af599586051
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Eric Horvitz
- Jaime Teevan
- Hema Raghavan
- Rosie Jones
- Diane Kelly
- Wiley Greiner
- Efthimis N. Efthimiadis
- Susan T. Dumais
In Information Systems
- Eric Horvitz
- Jaime Teevan
- Diane Kelly
- Susan T. Dumais
- Jeff Huang
- Efthimis N. Efthimiadis
- Rosie Jones
- Wiley Greiner
Citations in the corpus
- Potential for personalization (2010, methodology): “, via query suggestions [Anick 2003], interactive query expansion [Koenemann and Belkin 1996, Ruthven 2003], or filtering [Dumais et al.”
- Personalizing search via automated analysis of interests and activities (2005, background): “In practice, especially in Web search, explicit query refinement is rarely used [2].”
- Active Learning with Feedback on Features and Instances (2006, background): “Term level feedback has been studied in information retrieval (Anick, 2003; Croft and Das, 1990; Belkin et al., 2001).”
- Understanding user goals in web search (2004, background): “example) appears in the e right of the query are t appear when the query Beneath this is a table queries) that this user this case, we see that six r entered a new, more yntax suggests that this on a suggested query a [2, 3] assisted search ked on the first result, of the Kelly Blue Book w and used ”
- Methods for Evaluating Interactive Information Retrieval Systems with Users (2009, background): “to observe potential differences in performance [11].”
- Analyzing and evaluating query reformulation strategies in web search logs (2009, background): “For example, determining whether a query was a location reformulation as defined in [3] is subjective and would reduce the precision of our classifier.”
- Generating query substitutions (2006, background): “In an alternative to automatic query modification or expansion, one could allow the user to select the appropriate related terms [1].”