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OBOME - Ontology based opinion mining in UBIPOL
Ontologies have a special role in the UBIPOL system, they help to structure the policy related context, provide conceptualization for policy domain and use in the opinion mining process. In this work we presented a system called Ontology Based Opinion Mining Engine (OBOME) for analyzing a domain-specific opinion corpus by first assisting the user with the creation of a domain ontology from the corpus. We determined the polarity of opinion on the various domain aspects. In the former step, the policy domain aspect has are identified (namely which policy category is represented by the concept). This identification is supported by the policy modelling ontology, which describe the most important policy â related classes and structure. Then the most informative documents from the corpus are extracted and asked the user to create a set of aspects and related keywords using these documents. In the latter step, we used the corpus specific ontology to model the domain and extracted aspect-polarity associations using grammatical dependencies between words. Later, summarized results are shown to the user to analyze and store. Finally, in an offline process policy modeling ontology is updated
Interchanging lexical resources on the Semantic Web
Lexica and terminology databases play a vital role in many NLP applications, but currently most such resources are published in application-specific formats, or with custom access interfaces, leading to the problem that much of this data is in ââdata silosââ and hence difficult to access. The Semantic Web and in particular the Linked Data initiative provide effective solutions to this problem, as well as possibilities for data reuse by inter-lexicon linking, and incorporation of data categories by dereferencable URIs. The Semantic Web focuses on the use of ontologies to describe semantics on the Web, but currently there is no standard for providing complex lexical information for such ontologies and for describing the relationship between the lexicon and the ontology. We present our model, lemon, which aims to address these gap
Morphological Productivity in the Lexicon
In this paper we outline a lexical organization for Turkish that makes use of
lexical rules for inflections, derivations, and lexical category changes to
control the proliferation of lexical entries. Lexical rules handle changes in
grammatical roles, enforce type constraints, and control the mapping of
subcategorization frames in valency-changing operations. A lexical inheritance
hierarchy facilitates the enforcement of type constraints. Semantic
compositions in inflections and derivations are constrained by the properties
of the terms and predicates.
The design has been tested as part of a HPSG grammar for Turkish. In terms of
performance, run-time execution of the rules seems to be a far better
alternative than pre-compilation. The latter causes exponential growth in the
lexicon due to intensive use of inflections and derivations in Turkish.Comment: 10 pages LaTeX, {lingmacros,avm,psfig}.sty, 1 figure, 1 bibtex fil
Language resources and linked data: a practical perspective
Recently, experts and practitioners in language resources
have started recognizing the benefits of the linked data (LD) paradigm
for the representation and exploitation of linguistic data on the Web.
The adoption of the LD principles is leading to an emerging ecosystem of
multilingual open resources that conform to the Linguistic Linked Open
Data Cloud, in which datasets of linguistic data are interconnected and
represented following common vocabularies, which facilitates linguistic
information discovery, integration and access. In order to contribute to
this initiative, this paper summarizes several key aspects of the representation
of linguistic information as linked data from a practical perspective.
The main goal of this document is to provide the basic ideas and
tools for migrating language resources (lexicons, corpora, etc.) as LD on
the Web and to develop some useful NLP tasks with them (e.g., word
sense disambiguation). Such material was the basis of a tutorial imparted
at the EKAWâ14 conference, which is also reported in the paper
Mitigating response distortion in IS ethics research
Distributed construction of conceptual models may lead to a set of problems when these models are to
be compared or integrated. Different kinds of comparison conflicts are known (e.g. naming conflicts
or structural conflicts), the resolution of which is subject of different approaches. However, the expost resolution of naming conflicts raises subsequent problems that origin from semantic diversities of
namings â even if they are syntactically the same. Therefore, we propose an approach that allows for
avoiding naming conflicts in conceptual models already during modelling. This way, the ex-post
resolution of naming conflicts becomes obsolete. In order to realise this approach we combine domain
thesauri as lexical conventions for the use of terms, and linguistic grammars as conventions for valid
phrase structures. The approach is generic in order to make it reusable for any conceptual modelling
language
Unified Enterprise Knowledge Representation with Conceptual Models - Capturing Corporate Language in Naming Conventions
Conceptual modeling is an established instrument in the knowledge engineering process. However, a precondition for the usability of conceptual models is not only their syntactic correctness but also their semantic comparability. Assuring comparability is quite challenging especially when models are developed by different persons. Empirical studies show that such models can vary heavily, especially in model element naming, even if they are meant to express the same issue. In contrast to most ontology-driven approaches proposing the resolution of these differences ex-post, we introduce an approach that avoids naming differences in conceptual models already during modeling. Therefore we formalize naming conventions combining domain thesauri and phrase structures based on a linguistic grammar. This allows for guiding modelers automatically during the modeling process using standardized labels for model elements, thus assuring unified enterprise knowledge representation. Our approach is generic, making it applicable for any modeling language
The process of constructing ontological meaning based on criminal law verbs
This study intends to account for the process involved in the construction of the conceptual meaning of verbs (#EVENTS) directly related to legal aspects of terrorism and organized crime based on the evidence provided by the Globalcrimeterm Corpus and the consistent application of specific criteria for term extraction. The selected 49 concepts have eventually been integrated in the Core Ontology of FunGramKB (Functional Grammar Knowledge Base), a knowledge base which is founded on the principles of deep semantics and is also aimed at the computational development of the Lexical Constructional Model (www.fungramkb.com). To achieve this purpose, key phases of the COHERENT methodology (Periñån Pascual & Mairal Usón 2011) are followed, particularly those which involve the modelling, subsumption and hierarchisation of the aforementioned verbal concepts. The final outcome of this research shows that most of the apparently specialised conceptual units should eventually be included in the Core Ontology instead of the specific Globalcrimeterm Subontology, due to the fact that the semantic content of their corresponding lexical units can be found in widely used learner`s dictionaries and, consequently, this conceptual information is not only shared by the experts in the field but also by the layperson and the average speaker of the language
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