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Michelle LaMar

dblp:43/2771 · DBLP profile ↗
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4ranked-venue papers
1as first author
0since 2021 · last 2016
—ORCID · none

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

Artificial intelligence and machine learning · 3 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 3 · 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%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval › document processing › document analysis
document structure
0.011992
A Textual Object Management System · SIGIR 1992
Information retrieval › search engines
full-text search
0.011992
A Textual Object Management System · SIGIR 1992
YearPublicationVenuePosition
2016 Modifying Cognitive Load Component Survey for K-12 STEM Testing
Janet Koster van Groos, Michelle LaMar
CogSci3
2016 Assessing Science Inquiry using MDP Goal Detectors
Michelle LaMar, Janet Koster van Groos
CogSci1
2016 The Impact of Interactivity on Simulation-Based Science Inquiry with Variable-Setting Controls
Jung Aa Moon, Michelle LaMar, Carolyn Forsyth, Madeleine Keehner
CogSci2
1992 A Textual Object Management System
abstract
Computer programs that access significant amounts of text usually include code that manipulates the textual objects that comprise it. Such programs include electronic mail readers, typesetters and, in particular, full-text information retrieval systems. Such code is often unsatisfying in that access to textual objects is either efficient, or flexible, but not both. A programming language like Awk or Perl provides very general facilities for describing textual objects, but at the cost of rescanning the text for every textual object. At the other extreme, full-text information retrieval systems usually offer access to a very limited number of kinds of textual objects, but this access is very efficient. The system described in this paper is a programming tool for managing textual objects. It provides a great deal of flexibility, giving access to very complex document structure, with a large number of constituent kinds of textual objects. Further, it provides access to these objects very efficiently, both in terms of time and auxiliary space, by being very careful to access secondary storage only when absolutely necessary.
Scott C. Deerwester, Keith Waclena, Michelle LaMar
SIGIR3