PSYCHONET 2: contextualized and enriched psycholinguistic commonsense ontology

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

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PSYCHONET 2: contextualized and enriched psycholinguistic commonsense ontology
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Item Type:Conference or Workshop contribution (Paper)
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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 utilizingWordNet.
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.

Keywords:Psycholinguistic, Text Classification, Semantic Network, Commonsense Knowledgebase, Ontology Development
Subjects:G Mathematical and Computer Sciences > G700 Artificial Intelligence
G Mathematical and Computer Sciences > G400 Computer Science
G Mathematical and Computer Sciences > G720 Knowledge Representation
Divisions:College of Science > School of Computer Science
ID Code:4781
Deposited On:17 Nov 2011 09:31

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