Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Lee A. Appelbaum

dblp:61/2788 · DBLP profile ↗
← Back
6ranked-venue papers
0as first author
0since 2021 · last 1991
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 4Databases, data management, data science and information retrieval · 3

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
3 papers
Information retrieval · 80% Data mining · 20%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval
retrieval models
0.021990
An Architecture for Probabilistic Concept-Based Information Retrieval · SIGIR 1990
Conceptual Information Retrieval Using RUBRIC · SIGIR 1987
Data mining › predictive modeling › classification
decision tree learning
0.011991
Classification Trees for Information Retrieval · ML 1991
Information retrieval › document retrieval
concept-based retrieval
0.011990
An Architecture for Probabilistic Concept-Based Information Retrieval · SIGIR 1990
Information retrieval › retrieval models
probabilistic retrieval model
0.011990
An Architecture for Probabilistic Concept-Based Information Retrieval · SIGIR 1990
Information retrieval › search engines › semantic search
conceptual retrieval
0.011987
Conceptual Information Retrieval Using RUBRIC · SIGIR 1987
Information retrieval
indexing
0.011990
An Architecture for Probabilistic Concept-Based Information Retrieval · SIGIR 1990

Methods — techniques the papers use, named apart from their topics

probabilistic modeling · 0.0RUBRIC · 0.0
YearPublicationVenuePosition
1991 Classification Trees for Information Retrieval
Stuart L. Crawford, Robert M. Fung, Lee A. Appelbaum, Richard M. Tong
ML3
1990 An Architecture for Probabilistic Concept-Based Information Retrieval
abstract
Article An architecture for probabilistic concept-based information retrieval Share on Authors: R. M. Fung Advanced Decision Systems, 1500 Plymouth Street, Mountain View, California Advanced Decision Systems, 1500 Plymouth Street, Mountain View, CaliforniaView Profile , S. L. Crawford Advanced Decision Systems, 1500 Plymouth Street, Mountain View, California Advanced Decision Systems, 1500 Plymouth Street, Mountain View, CaliforniaView Profile , L. A. Appelbaum Advanced Decision Systems, 1500 Plymouth Street, Mountain View, California Advanced Decision Systems, 1500 Plymouth Street, Mountain View, CaliforniaView Profile , R. M. Tong Advanced Decision Systems, 1500 Plymouth Street, Mountain View, California Advanced Decision Systems, 1500 Plymouth Street, Mountain View, CaliforniaView Profile Authors Info & Claims SIGIR '90: Proceedings of the 13th annual international ACM SIGIR conference on Research and development in information retrievalDecember 1989 Pages 455–467https://doi.org/10.1145/96749.98252Online:01 December 1989Publication History 19citation520DownloadsMetricsTotal Citations19Total Downloads520Last 12 Months3Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Robert M. Fung, Stuart L. Crawford, Lee A. Appelbaum, Richard M. Tong
SIGIR3
1989 A knowledge representation for conceptual information retrieval
abstract
This article contains a detailed description of the knowledge representation used in RUBRIC, our concept-based, full-text information retrieval system. Since we view information retrieval as a process of evidential reasoning, the RUBRIC knowledge representation is designed to help maintain a clear distinction between descriptions of domain concepts, the documentary evidence for those concepts, and the beliefs about concepts that can be sustained on the basis of the evidence. This article is a consolidation of our earlier work in this area, containing, as it does, a revised language for defining concepts, an extended view of the role of evidence, and a formally grounded model of belief.
Richard M. Tong, Lee A. Appelbaum, Victor N. Askman
Int. J. Intell. Syst.2
1988 Problem structure and evidential reasoning
Richard M. Tong, Lee A. Appelbaum
Int. J. Approx. Reason.2
1987 Conceptual Information Retrieval Using RUBRIC
abstract
Article Free Access Share on Conceptual information retrieval using RUBRIC Authors: R. Tong Advanced Decision Systems, 201 San Antonio Circle, Suite 286, Mountain View, CA Advanced Decision Systems, 201 San Antonio Circle, Suite 286, Mountain View, CAView Profile , L. Appelbaum Advanced Decision Systems, 201 San Antonio Circle, Suite 286, Mountain View, CA Advanced Decision Systems, 201 San Antonio Circle, Suite 286, Mountain View, CAView Profile , V. Askman Advanced Decision Systems, 201 San Antonio Circle, Suite 286, Mountain View, CA Advanced Decision Systems, 201 San Antonio Circle, Suite 286, Mountain View, CAView Profile , J. Cunningham Advanced Decision Systems, 201 San Antonio Circle, Suite 286, Mountain View, CA Advanced Decision Systems, 201 San Antonio Circle, Suite 286, Mountain View, CAView Profile Authors Info & Claims SIGIR '87: Proceedings of the 10th annual international ACM SIGIR conference on Research and development in information retrievalNovember 1987 Pages 247–253https://doi.org/10.1145/42005.42033Online:01 November 1987Publication History 24citation577DownloadsMetricsTotal Citations24Total Downloads577Last 12 Months9Last 6 weeks2 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF
Richard M. Tong, Lee A. Appelbaum, Victor N. Askman, James F. Cunningham
SIGIR2
1986 Experiments with interval-valued uncertainty
Richard M. Tong, Lee A. Appelbaum
UAI2