Generating explanations for biomedical queries

Erdem, Esra; Öztok, Umut

doi:10.1017/s1471068413000598

Cited by 30 publications

(27 citation statements)

References 27 publications

(51 reference statements)

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“…To answer complex queries over a variety of biomedical ontologies (Erdem et al 2011), ASP allows us to extract relevant parts of them (thanks to external atoms) and integrate them by rules. For instance, the drug names can be extracted from a drug ontology, by first extracting the relevant triples from the ontology: Y, Z) and then extracting drug names from the triples:…”

Section: Integration Of Heterogeneous Knowledgementioning

confidence: 99%

“…the auxiliary concept of reachability of a gene from another gene by means of a chain of gene-gene interactions is required (Erdem et al 2011); this concept can be defined in ASP recursively as follows:…”

Section: Expressivity Of Representationmentioning

confidence: 99%

“…For instance, we can define that some drugs' toxicity is unknown as follows (Erdem et al 2011): unknownToxicityDrug(X) :-drugSynonym(R,X), not drugToxic(R), not -drugToxic(R).…”

Section: Expressivity Of Representationmentioning

confidence: 99%

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Applications of Answer Set Programming

2016

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A nswer set programming (ASP) is a knowledge representation and reasoning (KR) paradigm. It has rich highlevel representation languages that allow recursive definitions, aggregates, weight constraints, optimization statements, default negation, and external atoms. With such expressive languages, ASP can be used to declaratively represent knowledge (for example, mathematical models of problems, behaviour of dynamic systems, beliefs and actions of agents) and solve combinatorial search problems (for example, planning, diagnosis, phylogeny reconstruction) and knowledge-intensive problems (for example, query answering, explanation generation). The idea is to represent a problem as a "program" whose models (called "answer sets" Lifschitz 1988, 1991]

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Section: Integration Of Heterogeneous Knowledgementioning

confidence: 99%

Section: Expressivity Of Representationmentioning

confidence: 99%

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Applications of Answer Set Programming

2016

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“…Answer set programming has been used for syntactic parsing in the context of the Combinatory Categorial Grammar formalism (Lieler andSchüller 2012, Schüller 2013), for semantic parsing and representation of textual information (Baral et al 2011, Nguyen et al 2015, and for natural language understanding in the context of question answering (Tari and Baral 2005) and the Winograd Schema Challenge (Schüller 2014, Bailey et al 2015. In the context of controlled natural language processing, answer set programming has been used as a prototype of a rule system in the Attempto project (Kuhn 2007, Fuchs et al 2008, as a target language for biomedical queries related to drug discovery (Erdem and Yeniterzi 2009), as a source language for generating explanations for biomedical queries (Erdem andÖztok 2015), as a framework for human-robot interaction (Demirel et al 2016), and as a target language for writing executable specifications (Guy and Schwitter 2017).…”

Section: Answer Set Programming and Natural Language Processingmentioning

confidence: 99%

Specifying and Verbalising Answer Set Programs in Controlled Natural Language

Schwitter¹

2018

EasyChair Preprints

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We show how a bi-directional grammar can be used to specify and verbalise answer set programs in controlled natural language. We start from a program specification in controlled natural language and translate this specification automatically into an executable answer set program. The resulting answer set program can be modified following certain naming conventions and the revised version of the program can then be verbalised in the same subset of natural language that was used as specification language. The bi-directional grammar is parametrised for processing and generation, deals with referring expressions, and exploits symmetries in the data structure of the grammar rules whenever these grammar rules need to be duplicated. We demonstrate that verbalisation requires sentence planning in order to aggregate similar structures with the aim to improve the readability of the generated specification. Without modifications, the generated specification is always semantically equivalent to the original one; our bi-directional grammar is the first one that allows for semantic round-tripping in the context of controlled natural language processing.

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“…Indeed, ASP combines a comparatively high knowledge-modeling power [10] with a robust solving technology [2,4,12,24,26,27,37,38]. For these reasons ASP has become an established logic-based programming paradigm with successful applications to complex problems in Artificial Intelligence [7,23], Bioinformatics [13,18,21], Databases [36,39], Game Theory [6]; more recently ASP has been applied to solve industrial applications [29,17].…”

Section: Introductionmentioning

confidence: 99%

On the Application of Answer Set Programming to the Conference Paper Assignment Problem

Amendola

Dodaro

Leone

et al. 2016

AI*IA 2016 Advances in Artificial Intelligence

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Abstract. Among the tasks to be carried out by conference organizers is the one of assigning reviewers to papers. That problem is known in the literature as the Conference Paper Assignment Problem (CPAP). In this paper we approach the solution of a reasonably rich variant of the CPAP by means of Answer Set Programming (ASP). ASP is an established logic-based programming paradigm which has been successfully applied for solving complex problems arising in Artificial Intelligence. We show how the CPAP can be elegantly encoded by means of an ASP program, and we analyze the results of an experiment, conducted on real-world data, that outlines the viability of our solution.

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Generating explanations for biomedical queries

Cited by 30 publications

References 27 publications

Applications of Answer Set Programming

Applications of Answer Set Programming

Specifying and Verbalising Answer Set Programs in Controlled Natural Language

On the Application of Answer Set Programming to the Conference Paper Assignment Problem

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