Journal ArticleDOI
Automatic construction of a large-scale situation ontology by mining how-to instructions from the web
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TLDR
This paper proposes an approach to automatically constructing a large- scale situation ontology by mining large-scale web resources, eHow and wikiHow, which contain an enormous amount of how-to instructions.About:
This article is published in Journal of Web Semantics.The article was published on 2010-07-01. It has received 65 citations till now. The article focuses on the topics: Ontology (information science) & Ontology-based data integration.read more
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Proceedings Article
Choice of Plausible Alternatives: An Evaluation of Commonsense Causal Reasoning
TL;DR: The Choice Of Plausible Alternatives (COPA) evaluation as discussed by the authors uses a forced-choice format, where each question gives a premise and two plausible causes or effects, where the correct choice is the alternative that is more plausible than the other.
Proceedings Article
SemEval-2012 Task 7: Choice of Plausible Alternatives: An Evaluation of Commonsense Causal Reasoning
TL;DR: The two systems that competed in this task as part of SemEval-2012 are described, and their results are compared to those achieved in previously published research.
Book ChapterDOI
Integrating Know-How into the Linked Data Cloud
TL;DR: In this paper, the authors present a framework for integrating procedural knowledge into the Linked Data Cloud, which allows the automatic generation of links between different know-how resources and other online knowledge bases, such as DBpedia.
Crowdsourcing Narrative Intelligence
TL;DR: In this paper, a novel technique for automatically learning script-like narrative knowledge from crowdsourcing is described, which leverages human workers' collective understanding of social and procedural constructs to learn a potentially unlimited range of scripts regarding how real-world situations unfold.
Journal ArticleDOI
Concept relation extraction using Naïve Bayes classifier for ontology-based question answering systems
G. Suresh Kumar,G. Zayaraz +1 more
TL;DR: An algorithm to iteratively extract a list of attributes and associations for the given seed concept from which the rough schema is conceptualized using a syntactic and semantic probability-based Naive Bayes classifier is proposed.
References
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Proceedings ArticleDOI
Context-Aware Computing Applications
TL;DR: This paper describes systems that examine and react to an individual's changing context, and describes four catagories of context-aware applications: proximate selection, automatic contextual reconfiguration, contextual information and commands, and contex-triggered actions.
Proceedings ArticleDOI
Automatic acquisition of hyponyms from large text corpora
TL;DR: A set of lexico-syntactic patterns that are easily recognizable, that occur frequently and across text genre boundaries, and that indisputably indicate the lexical relation of interest are identified.
Proceedings Article
DAML-S: semantic markup for web services
Anupriya Ankolekar,Mark Burstein,Jerry R. Hobbs,Ora Lassila,David Martin,Sheila A. McIlraith,Srini Narayanan,Massimo Paolucci,Terry R. Payne,Katia Sycara,Honglei Zeng +10 more
TL;DR: The overall structure of the ontology, the service profile for advertising services, and the process model for the detailed description of the operation of services are described, which compare DAML-S with several industry efforts to define standards for characterizing services on the Web.
Proceedings Article
Open information extraction from the web
TL;DR: Open Information Extraction (OIE) as mentioned in this paper is a new extraction paradigm where the system makes a single data-driven pass over its corpus and extracts a large set of relational tuples without requiring any human input.
Proceedings ArticleDOI
Snowball: extracting relations from large plain-text collections
Eugene Agichtein,Luis Gravano +1 more
TL;DR: This paper develops a scalable evaluation methodology and metrics for the task, and presents a thorough experimental evaluation of Snowball and comparable techniques over a collection of more than 300,000 newspaper documents.