Miller, Tristan ; Agne, Stefan (2005)
Attention-based Information Retrieval Using Eye Tracker Data.
doi: 10.1145/1088622.1088672
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
We describe eFISK, an automated keyword extraction system which unobtrusively measures the user's attention in order to isolate and identify those areas of a written document the reader finds of greatest interest. Attention is measured by use of eye-tracking hardware consisting of a desk-mounted infrared camera which records various data about the user's eye. The keywords thus identified are subsequently used in the back end of an information retrieval system to help the user find other documents which contain information of interest to him. Unlike traditional IR techniques which compare documents simply on the basis of common terms withal, our system also accounts for the weights users implicitly attach to certain words or sections of the source document. We describe a task-based user study which compares the utility of standard relevance feedback techniques to the keywords and keyphrases discovered by our system in finding other relevant documents from a corpus.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2005 |
| Autor(en): | Miller, Tristan ; Agne, Stefan |
| Art des Eintrags: | Bibliographie |
| Titel: | Attention-based Information Retrieval Using Eye Tracker Data |
| Sprache: | Englisch |
| Publikationsjahr: | 2005 |
| Buchtitel: | Proceedings of the Third International Conference on Knowledge Capture (K-CAP05) |
| DOI: | 10.1145/1088622.1088672 |
| URL / URN: | https://dx.doi.org/10.1145/1088622.1088672 |
| Zugehörige Links: | |
| Kurzbeschreibung (Abstract): | We describe eFISK, an automated keyword extraction system which unobtrusively measures the user's attention in order to isolate and identify those areas of a written document the reader finds of greatest interest. Attention is measured by use of eye-tracking hardware consisting of a desk-mounted infrared camera which records various data about the user's eye. The keywords thus identified are subsequently used in the back end of an information retrieval system to help the user find other documents which contain information of interest to him. Unlike traditional IR techniques which compare documents simply on the basis of common terms withal, our system also accounts for the weights users implicitly attach to certain words or sections of the source document. We describe a task-based user study which compares the utility of standard relevance feedback techniques to the keywords and keyphrases discovered by our system in finding other relevant documents from a corpus. |
| ID-Nummer: | TUD-CS-2005-0040 |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Ubiquitäre Wissensverarbeitung |
| Hinterlegungsdatum: | 31 Dez 2016 14:29 |
| Letzte Änderung: | 23 Aug 2018 11:41 |
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