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Timo Soininen

dblp:48/6773 · DBLP profile ↗
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6ranked-venue papers
1as first author
0since 2021 · last 2007
—ORCID · none

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

Artificial intelligence and machine learning · 5 · 1 first-authorSoftware engineering, systems software and programming languages · 2 · 1 first-authorDatabases, data management, data science and information retrieval · 2Theory of computation · 1Applied, interdisciplinary, general and emerging computing · 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.

Artificial intelligence
1 paper
Knowledge representation and reasoning · 100%

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

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Knowledge representation and reasoning
logic-based reasoning
0.012002
Extending and implementing the stable model semantics · Artif. Intell. 2002
Knowledge, reasoning and agents › Knowledge representation and reasoning › logic programming
stable model semantics
0.012002
Extending and implementing the stable model semantics · Artif. Intell. 2002
YearPublicationVenuePosition
2007 Kumbang: A domain ontology for modelling variability in software product families
Timo Asikainen, Tomi Männistö, Timo Soininen
Adv. Eng. Informatics3
2006 A Unified Conceptual Foundation for Feature Modelling
abstract
Feature modelling has become perhaps the most popular method for representing variabilities and commonalities in software product families. A large number of feature modelling methods and supporting tools have been reported. The conceptual foundation of feature models remains vague, a fact that severely undermines the usability of feature models. Therefore, we introduce Forfamel, a rigorous conceptual foundation for feature modelling. Forfamel synthesises existing feature modelling methods in the sense that it covers most concepts and constructs found in existing feature modelling methods. In addition, Forfamel includes a few additional constructs that may prove to be useful. We show the novel contribution of Forfamel by reflecting it against previous feature modelling methods and arguing for its underlying design decisions
Timo Asikainen, Tomi Männistö, Timo Soininen
SPLC3
2002 Extending and implementing the stable model semantics
Patrik Simons, Ilkka Niemelä, Timo Soininen
Artif. Intell.3
2001 Multiple abstraction levels in modelling product structures
Tomi Männistö, Hannu Peltonen, Timo Soininen, Reijo Sulonen
Data Knowl. Eng.3
1999 A Fixpoint Definition of Dynamic Constraint Satisfaction
Timo Soininen, Esther M. Gelle, Ilkka Niemelä
CP1
1999 Stable Model Semantics of Weight Constraint Rules
Ilkka Niemelä, Patrik Simons, Timo Soininen
LPNMR3