Abstract
In this study, we develop a fast and comprehensive literature search tool for IS community. We first propose a novel citation recommendation method, which produces a list of relevant references given the input of a long query. In our method, we introduce a new feature of aggregate likelihood being cited, which captures the wisdom of crowds in the reference lists of academic articles, in addition to the topical similarity. The method has achieved better efficiency and accuracy on a standard dataset compared with existing methods. Next, we construct a citation network within the three top IS journals (i.e., ISR, JMIS, and MISQ). Finally, we plan to implement the proposed method on ISTopic.org, an online platform for the exploration of research topics. To further evaluate the performance of the literature search tool, we plan to conduct a user study to compare the usability of our tool with existing literature search tools.
| Original language | English |
|---|---|
| Title of host publication | ICIS 2017: Transforming Society with Digital Innovation |
| Publisher | Association for Information Systems |
| ISBN (Print) | 9780996683159 |
| Publication status | Published - 2017 |
| Externally published | Yes |
| Event | 38th International Conference on Information Systems (ICIS 2017): Transforming Society with Digital Innovation - COEX, Convention and Exhibition Center, Seoul, Korea, Republic of Duration: 10 Dec 2017 → 13 Dec 2017 http://icis2017.aisnet.org/ http://icis2017.aisnet.org/wp-content/uploads/2017/12/ICIS2017_ProgramBook_1209.pdf |
Publication series
| Name | ICIS 2017: Transforming Society with Digital Innovation |
|---|
Conference
| Conference | 38th International Conference on Information Systems (ICIS 2017) |
|---|---|
| Place | Korea, Republic of |
| City | Seoul |
| Period | 10/12/17 → 13/12/17 |
| Internet address |
Bibliographical note
Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].Funding
The work described in this paper was partially supported by a grant from the National Natural Science Foundation of China (Grant No: 71471157) and research grant from Digital Innovation Laboratory, Department of Information Systems, City University of Hong Kong.
Research Keywords
- Citation graph
- Literature search
- Topic model
- Wisdom of crowds
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