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TileBars: visualization of term distribution information in full text information access
Abstract
The field of information retrieval has traditionally focused on textbases consisting of titles and abstracts. As a consequence, many underlying assumptions must be altered for retrieval from full-length text collections. This paper argues for making use of text structure when retrieving from full text documents, and presents a visualization paradigm, called TileBars, that demonstrates the usefulness of explicit term distribution information in Boolean-type queries. TileBars simultaneously and compactly indicate relative document length, query term frequency, and query term distribution. The patterns in a column of TileBars can be quickly scanned and deciphered, aiding users in making judgments about the potential relevance of the retrieved documents.
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Citations
Cited by
Exploratory search: from finding to understanding
Marchionini, G. (2006) · Communications of the ACM · doi:10.1145/1121949.1121979 · Cited by 1,506
Interactive Intent Modeling for Exploratory Search
Ruotsalo, T., Peltonen, J., Eugster, M. J. A., Głowacka, D., Floréen, P., Myllymäki, P., Jacucci, G., & Kaski, S. (2018) · ACM Transactions on Information Systems · doi:10.1145/3231593 · Cited by 57
Metadata
- Authors
- Hearst, M. A.
- Venue
- Proceedings of the SIGCHI conference on Human factors in computing systems - CHI '95
- Publisher
- ACM Press
- Published
- 1995
- Pages
- 59-66
- OpenAlex
- W2158231614
- Cited by
- 555
- References
- 0
- FWCI
- 28.00
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: TileBars: visualization of term distribution information in full text information access. https://app.cochat.ai/papers/10.1145/223904.223912
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- Hearst, M. A. (1995). TileBars: visualization of term distribution information in full text information access. Proceedings of the SIGCHI conference on Human factors in computing systems - CHI '95. https://doi.org/10.1145/223904.223912
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
