John M. Zelle

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6ranked-venue papers

5as 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 · 4 · 4 first-authorGraphics, computer vision, multimedia, augmented reality and games · 3 · 3 first-authorHuman-computer interaction and ubiquitous computing · 2 · 1 first-author

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.

Software engineering, system software, and programming languages 2 papers		Program synthesis and code generation · 57% Compilers and program optimization · 33% Empirical software engineering · 10%
Artificial intelligence 2 papers		Knowledge representation and reasoning · 100%
Theoretical computer science 3 papers		Automata and formal languages · 59% Logic in computer science · 41%

Topics — the 8 heaviest of 9, each with the papers that count most for it

Topic	Papers	Last	Evidence papers
Automata and formal languages grammatical inference	2	1994	Inducing Deterministic Prolog Parsers from Treebanks: A Machine Learning Approach · AAAI 1994 Learning Semantic Grammars with Constructive Inductive Logic Programming · AAAI 1993
Knowledge, reasoning and agents › Knowledge representation and reasoning › logic programming inductive logic programming	1	1994	Combining Top-down and Bottom-up Techniques in Inductive Logic Programming · ICML 1994
Knowledge, reasoning and agents › Knowledge representation and reasoning logic-based reasoning	1	1994	Combining Top-down and Bottom-up Techniques in Inductive Logic Programming · ICML 1994
Compilers and program optimization › parsing parser generation	1	1994	Inducing Deterministic Prolog Parsers from Treebanks: A Machine Learning Approach · AAAI 1994
Program synthesis and code generation › inductive logic programming constructive induction	1	1993	Learning Semantic Grammars with Constructive Inductive Logic Programming · AAAI 1993
Program synthesis and code generation inductive logic programming	1	1993	Learning Semantic Grammars with Constructive Inductive Logic Programming · AAAI 1993
Logic in computer science logic programming	1	1993	Combining FOIL and EBG to Speed-up Logic Programs · IJCAI 1993
Empirical software engineering › AI for software engineering machine learning for software engineering	1	1994	Inducing Deterministic Prolog Parsers from Treebanks: A Machine Learning Approach · AAAI 1994

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

inductive logic programming · 0.0treebank-based induction · 0.0machine learning · 0.0FOIL · 0.0EBG · 0.0

Year	Publication	Venue	Position
2006	Successful approaches to teaching introductory computer science courses with python abstract No abstract available. David Ranum, Bradley N. Miller, John M. Zelle, Mark Guzdial	SIGCSE	3
2004	Simple, low-cost stereographics: VR for everyone abstract Students are very interested in cutting-edge technologies like virtual reality (VR), and VR has many potential uses in education. However, building VR applications has proved challenging due to both cost and technical skill barriers. Through a series of experiments in "shoestring" VR, we have developed methods of bringing an important facet of VR, stereoscopic display, to our students in a simple, cost-effective way. This paper describes our approach. John M. Zelle, Charles Figura	SIGCSE	1
1994	Inducing Deterministic Prolog Parsers from Treebanks: A Machine Learning Approach John M. Zelle, Raymond J. Mooney	AAAI	1
1994	Combining Top-down and Bottom-up Techniques in Inductive Logic Programming John M. Zelle, Raymond J. Mooney, Joshua B. Konvisser	ICML	1
1993	Learning Semantic Grammars with Constructive Inductive Logic Programming John M. Zelle, Raymond J. Mooney	AAAI	1
1993	Combining FOIL and EBG to Speed-up Logic Programs John M. Zelle, Raymond J. Mooney	IJCAI	1