Abstract
| Language | Undefined |
|---|---|
| Title of host publication | Active media technology |
| Place of Publication | Berlin |
| Publisher | Springer Verlag |
| Pages | 395-402 |
| Number of pages | 8 |
| ISBN (Print) | 9783642154706 |
| DOIs | |
| State | Published - 28 Aug 2010 |
Publication series
| Name | Lecture Notes in Computer Science |
|---|---|
| Publisher | Springer Verlag |
| No. | 6335 |
| Volume | 6335 |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Keywords
- IR-75070
- METIS-276165
- Adaptive Information Retrieval
- Knowledge Model
- HMI-HF: Human Factors
- Similarity Metric
- EWI-18892
- HMI-SLT: Speech and Language Technology
- HMI-IE: Information Engineering
- User Profile
Cite this
}
Modeling User Knowledge from Queries: Introducing a Metric for Knowledge. / van der Sluis, Frans; van den Broek, Egon.
Active media technology. Berlin : Springer Verlag, 2010. p. 395-402 (Lecture Notes in Computer Science; Vol. 6335, No. 6335).Research output: Chapter in Book/Report/Conference proceeding › Chapter
TY - CHAP
T1 - Modeling User Knowledge from Queries: Introducing a Metric for Knowledge
AU - van der Sluis,Frans
AU - van den Broek,Egon
N1 - 10.1007/978-3-642-15470-6_41
PY - 2010/8/28
Y1 - 2010/8/28
N2 - The user's knowledge plays a pivotal role in the usability and experience of any information system. Based on a semantic network and query logs, this paper introduces a metric for users' knowledge on a topic. The finding that people often return to several sets of closely related, well-known, topics, leading to certain concentrated, highly activated areas in the semantic network, forms the core of this metric. Tests were performed determining the knowledgeableness of 32,866 users on in total 8 topics, using a data set of more than 6 million queries. The tests indicate the feasibility and robustness of such a user-centered indicator.
AB - The user's knowledge plays a pivotal role in the usability and experience of any information system. Based on a semantic network and query logs, this paper introduces a metric for users' knowledge on a topic. The finding that people often return to several sets of closely related, well-known, topics, leading to certain concentrated, highly activated areas in the semantic network, forms the core of this metric. Tests were performed determining the knowledgeableness of 32,866 users on in total 8 topics, using a data set of more than 6 million queries. The tests indicate the feasibility and robustness of such a user-centered indicator.
KW - IR-75070
KW - METIS-276165
KW - Adaptive Information Retrieval
KW - Knowledge Model
KW - HMI-HF: Human Factors
KW - Similarity Metric
KW - EWI-18892
KW - HMI-SLT: Speech and Language Technology
KW - HMI-IE: Information Engineering
KW - User Profile
U2 - 10.1007/978-3-642-15470-6_41
DO - 10.1007/978-3-642-15470-6_41
M3 - Chapter
SN - 9783642154706
T3 - Lecture Notes in Computer Science
SP - 395
EP - 402
BT - Active media technology
PB - Springer Verlag
CY - Berlin
ER -