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William B. Richmond

dblp:55/5550 · DBLP profile ↗
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3ranked-venue papers
1as first author
0since 2021 · last 1997
—ORCID · none

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

Artificial intelligence and machine learning · 2 · 1 first-authorDatabases, data management, data science and information retrieval · 1

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
1 paper
Information retrieval · 100%
Theoretical computer science
1 paper
Algorithms and data structures · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval › retrieval models
decision-theoretic retrieval		 0.011990
A Decision-Theoretic Approach to Information Retrieval · ACM Trans. Database Syst. 1990
Information retrieval › search engines
file search		 0.011990
A Decision-Theoretic Approach to Information Retrieval · ACM Trans. Database Syst. 1990
Information retrieval
retrieval models		 0.011990
A Decision-Theoretic Approach to Information Retrieval · ACM Trans. Database Syst. 1990
Algorithms and data structures
dynamic programming		 0.011990
A Decision-Theoretic Approach to Information Retrieval · ACM Trans. Database Syst. 1990

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

dynamic programming · 0.0decision theory · 0.0
YearPublicationVenuePosition
1997 Introduction to the special issue on economics of information systems
Anitesh Barua, William B. Richmond
 Decis. Support Syst.2
1992 Incomplete contracting issues in information systems development outsourcing
William B. Richmond, Abraham Seidmann, Andrew B. Whinston
 Decis. Support Syst.1
1990 A Decision-Theoretic Approach to Information Retrieval
abstract
We present the file search problem in a decision-theoretic framework, and discuss a variation of it that we call the common index problem. The goal of the common index problem is to return the best available record in the file, where best is in terms of a class of user preferences. We use dynamic programming to construct an optimal algorithm using two different optimality criteria, and we develop sufficient conditions for obtaining complete information.
James C. Moore, William B. Richmond, Andrew B. Whinston
 ACM Trans. Database Syst.2