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PSYCHONET 2: contextualized and enriched psycholinguistic commonsense ontology

Mohtasseb Billah, Haytham, Ahmed, Amr, Altadmri, Amjad, Cobham, David (2011) PSYCHONET 2: contextualized and enriched psycholinguistic commonsense ontology. In: International Conference on Knowledge Engineering and Ontology Development (KEOD), 25 - 29 October 2011, Paris, France.

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PsychoNet 1 has demonstrated the feasibility of integrating psycholinguistic taxonomy, represented in LIWC, and its semantic textual representation in the form of commonsense ontology, represented in ConceptNet. However, various limitations exist in PsychoNet 1, including the lack of concluding context of the concept annotation. In this paper, we address most of those limitations and introduce a new enhanced and enriched version, PsychoNet 2. PsychoNet 2 utilizes WordNet, in addition to LIWC and ConceptNet, to produce an integrated contextualized psycholinguistic ontology. The first and the main contribution is that, in PsychoNet 2, each concept is annotated by the potential (most representative) contextual psycholinguistic categories, rather than all applicable categories. The second contribution is the enrichment of LIWC through utilizing WordNet. This in fact produced an enriched version of LIWC that may also be used independently in other applications. This has contributed to substantial enrichment of PsychoNet 2 as it facilitated including additional number of concepts that were not included in PsychoNet 1 due to lack of corresponding words in the original LIWC. A sample application of text classification, for a mood prediction task, is presented to demonstrate the introduced enhancements. The results confirm the improved performance of the new PsychoNet 2 against PsychoNet 1.

Item Type: Conference or workshop item (Paper)
Uncontrolled keywords: Psycholinguistic, Text Classification, Semantic Network, Commonsense Knowledgebase, Ontology Development
Subjects: Q Science > Q Science (General) > Q335 Artificial intelligence
Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, > QA76.76.E95 Expert Systems (Intelligent Knowledge Based Systems)
Divisions: Faculties > Sciences > School of Computing
Faculties > Sciences > School of Computing > Computational Intelligence Group
Depositing User: Amjad Altadmri
Date Deposited: 15 Jan 2015 22:34 UTC
Last Modified: 29 May 2019 13:53 UTC
Resource URI: (The current URI for this page, for reference purposes)
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