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Gregory Marton

dblp:95/306 · DBLP profile ↗
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4ranked-venue papers
2as first author
0since 2021 · last 2006
—ORCID · none

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

Artificial intelligence and machine learning · 3 · 2 first-authorDatabases, data management, data science and information retrieval · 2

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%
Artificial intelligence
1 paper
Question answering and dialogue systems · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Natural language and speech › Question answering and dialogue systems
passage retrieval
0.012003
Quantitative evaluation of passage retrieval algorithms for question answering · SIGIR 2003
Information retrieval › document retrieval
passage retrieval
0.012003
Quantitative evaluation of passage retrieval algorithms for question answering · SIGIR 2003
Information retrieval
evaluation
0.012003
Quantitative evaluation of passage retrieval algorithms for question answering · SIGIR 2003

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

density-based scoring · 0.1boolean querying · 0.1
YearPublicationVenuePosition
2006 Using Semantic Overlap Scoring in Answering TREC Relationship Questions
Gregory Marton, Boris Katz
LREC1
2006 Nuggeteer: Automatic Nugget-Based Evaluation using Descriptions and Judgements
Gregory Marton, Alexey Radul
HLT-NAACL1
2003 Quantitative evaluation of passage retrieval algorithms for question answering
abstract
Passage retrieval is an important component common to many question answering systems. Because most evaluations of question answering systems focus on end-to-end performance, comparison of common components becomes di#cult. To address this shortcoming, we present a quantitative evaluation of various passage retrieval algorithms for question answering, implemented in a framework called Pauchok. We present three important findings: Boolean querying schemes perform well in the question answering task. The performance di#erences between various passage retrieval algorithms vary with the choice of document retriever, which suggests significant interactions between document retrieval and passage retrieval. The best algorithms in our evaluation employ density-based measures for scoring query terms. Our results reveal future directions for passage retrieval and question answering.
Stefanie Tellex, Boris Katz, Jimmy Lin, Aaron Fernandes, Gregory Marton
SIGIR5
2002 Omnibase: Uniform Access to Heterogeneous Data for Question Answering
Boris Katz, Sue Felshin, Deniz Yuret, Ali Ibrahim, Jimmy Lin, Gregory Marton, Alton Jerome McFarland, Baris Temelkuran
NLDB6