Daniel Billsus
- Information Systems top 0.2%
- Recommender Systems and Techniques 9
- Web Data Mining and Analysis 4
- Data Mining Algorithms and Applications 4
- Artificial Intelligence top 1%
- Machine Learning and Algorithms 3
- Topic Modeling 3
- Signal Processing top 2%
- Data Management and Algorithms 3
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- Peer-to-Peer Network Technologies 3
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- Personal Information Management and User Behavior 3
- Co-authors
- Michael J. PazzaniJack MuramatsuGeoffrey I. WebbClifford BrunkDavid M. HilbertJames ChenDan Maynes-AminzadeLaurent Denoue
- Journals
- User Modeling and User-Adapted Interaction (2 papers)Communications of the ACM (1 paper)AI Magazine (1 paper)
- Partner nations
- United StatesAustralia
In The Last Decade
Daniel Billsus
20 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 102
- Information Systems 2.1k
- Artificial Intelligence 1.2k
- Computer Vision and Pattern Recognition 778
- Signal Processing 377
- Computer Science Applications 151
Countries citing papers authored by Daniel Billsus
This map shows the geographic impact of Daniel Billsus's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniel Billsus with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Billsus more than expected).
Fields of papers citing papers by Daniel Billsus
This network shows the impact of papers produced by Daniel Billsus. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniel Billsus. The network helps show where Daniel Billsus may publish in the future.
Co-authorship network
The 20 scholars most cited alongside Daniel Billsus, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 3 | |
| 2 | Seamless Capture and Discovery for Corporate Memory | 2006 | 8 |
| 3 | ProjectorBox: Seamless presentation capture for classrooms | 2005 | 10 |
| 4 | 2005 | 4 | |
| 5 | 2005 | 42 | |
| 6 | 2004 | 6 | |
| 7 | 2002 | 158 | |
| 8 | 2002 | 31 | |
| 9 | 2001 | 219 | |
| 10 | 2000 | 61 | |
| 11 | 2000 | 304 | |
| 12 | 1999 | 138 | |
| 13 | 1999 | 12 | |
| 14 | Evaluating Adaptive Web Site Agents | 1999 | 4 |
| 15 | Learning Collaborative Information Filtersbreakdown → | 1998 | 656 |
| 16 | 1998 | 21 | |
| 17 | 1997 | 22 | |
| 18 | Learning and Revising User Profiles: The Identification of Interesting Web Sitesbreakdown → | 1997 | 758 |
| 19 | Syskill & webert: Identifying interesting web sites | 1996 | 384 |
| 20 | Revising User Profiles: The Search for Interesting Web Sites | 1996 | 12 |
About Daniel Billsus
Daniel Billsus is a scholar working on Information Systems, Information Systems and Management and Artificial Intelligence, having authored 20 papers that have together received 2.9k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (9 papers), Web Data Mining and Analysis (4 papers), Data Mining Algorithms and Applications (4 papers), Peer-to-Peer Network Technologies (3 papers), Personal Information Management and User Behavior (3 papers), Machine Learning and Algorithms (3 papers), Topic Modeling (3 papers) and Data Management and Algorithms (3 papers). The work is most often cited by research in Information Systems (2.1k citations), Artificial Intelligence (1.2k citations) and Computer Vision and Pattern Recognition (778 citations). Daniel Billsus has collaborated with scholars based in United States and Australia. Frequent co-authors include Michael J. Pazzani, Jack Muramatsu, Geoffrey I. Webb, Clifford Brunk, David M. Hilbert, James Chen, Dan Maynes-Aminzade, Laurent Denoue, John Adcock and Matthew Cooper. Their work appears in journals such as User Modeling and User-Adapted Interaction, Communications of the ACM, AI Magazine, Autonomous Agents and Multi-Agent Systems and Journal of the American Podiatric Medical Association.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.