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1
ALONE: A Dataset for Toxic Behavior among Adolescents on Twitter
In: Publications (2020)
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2
Personalized Prediction of Suicide Risk for Web-based Intervention
In: Krishnaprasad Thirunarayan (2019)
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3
Personalized Prediction of Suicide Risk for Web-based Intervention
In: Amit P. Sheth (2019)
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4
Personalized Prediction of Suicide Risk for Web-based Intervention
In: Kno.e.sis Publications (2018)
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5
Intent Classification of Short-Text on Social Media
In: Valerie Shalin (2017)
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6
Intent Classification of Short-Text on Social Media
In: Amit P. Sheth (2016)
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7
Intent Classification of Short-Text on Social Media
In: Krishnaprasad Thirunarayan (2016)
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8
Intent Classification of Short-Text on Social Media
In: Publications (2015)
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9
Intent Classification of Short-Text on Social Media
In: Publications (2015)
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10
FACES: Diversity-Aware Entity Summarization using Incremental Hierarchical Conceptual Clustering
In: Kno.e.sis Publications (2015)
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11
Context-Driven Automatic Subgraph Creation for Literature-Based Discovery
In: Kno.e.sis Publications (2015)
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12
Intent Classification of Short-Text on Social Media
In: Kno.e.sis Publications (2015)
Abstract: Social media platforms facilitate the emergence of citizen communities that discuss real-world events. Their content reflects a variety of intent ranging from social good (e.g., volunteering to help) to commercial interest (e.g., criticizing product features). Hence, mining intent from social data can aid in filtering social media to support organizations, such as an emergency management unit for resource planning. However, effective intent mining is inherently challenging due to ambiguity in interpretation, and sparsity of relevant behaviors in social data. In this paper, we address the problem of multiclass classification of intent with a use-case of social data generated during crisis events. Our novel method exploits a hybrid feature representation created by combining top-down processing using knowledge-guided patterns with bottom-up processing using a bag-of-tokens model. We employ pattern-set creation from a variety of knowledge sources including psycholinguistics to tackle the ambiguity challenge, social behavior about conversations to enrich context, and contrast patterns to tackle the sparsity challenge. Our results show a significant absolute gain up to 7% in the F1 score relative to a baseline using bottom-up processing alone, within the popular multiclass frameworks of One-vs-One and One-vs-All. Intent mining can help design efficient cooperative information systems between citizens and organizations for serving organizational information needs.
Keyword: Bioinformatics; Communication; Communication Technology and New Media; Computer Sciences; Contrast Mining; Crisis Informatics; Databases and Information Systems; Declaritive Knowledge; Intent Mining; Life Sciences; OS and Networks; Physical Sciences and Mathematics; Psycholinguistics; Science and Technology Studies; Social and Behavioral Sciences; Social Media
URL: https://corescholar.libraries.wright.edu/knoesis/1081
https://corescholar.libraries.wright.edu/cgi/viewcontent.cgi?article=2460&context=knoesis
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13
iExplore: Interactive Browsing and Exploring Biomedical Knowledge
In: Amit P. Sheth (2014)
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14
FACES: Diversity-Aware Entity Summarization using Incremental Hierarchical Conceptual Clustering
In: Amit P. Sheth (2014)
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15
A Graph-Based Recovery and Decomposition of Swanson’s Hypothesis using Semantic Predications
In: Krishnaprasad Thirunarayan (2014)
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16
Context-Driven Automatic Subgraph Creation for Literature-Based Discovery
In: Amit P. Sheth (2014)
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17
FACES: Diversity-Aware Entity Summarization using Incremental Hierarchical Conceptual Clustering
In: Krishnaprasad Thirunarayan (2014)
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18
Expressive Extensions to Inheritance Networks
In: Krishnaprasad Thirunarayan (2014)
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19
On the Declarative Semantics of Inheritance Networks
In: Krishnaprasad Thirunarayan (2014)
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20
Inheritance in Programming Languages
In: Krishnaprasad Thirunarayan (2014)
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