Human-Computer text conversation through NLP in Tamil using Intent Recognition

2019 ◽  
Author(s):  
Udhayakumar Shanmugam ◽  
Sowjanya Mani ◽  
Sneha Sivakumar ◽  
P. Rajeswari
Keyword(s):  
Intent Recognition ◽  
Computer Text

Reports of the Workshops Held at the 2019 AAAI Conference on Artificial Intelligence

AI Magazine ◽  
2019 ◽  
Vol 40 (3) ◽  
pp. 67-78
Author(s):  
Guy Barash ◽  
Mauricio Castillo-Effen ◽  
Niyati Chhaya ◽  
Peter Clark ◽  
Huáscar Espinoza ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Language Processing ◽  
Cyber Security ◽  
Question Answering ◽  
Intent Recognition ◽  
Affective Content ◽  
Learning Plan ◽  
Dialog System ◽  
Affective Content Analysis ◽  
Games And Simulations

The workshop program of the Association for the Advancement of Artificial Intelligence’s 33rd Conference on Artificial Intelligence (AAAI-19) was held in Honolulu, Hawaii, on Sunday and Monday, January 27–28, 2019. There were fifteen workshops in the program: Affective Content Analysis: Modeling Affect-in-Action, Agile Robotics for Industrial Automation Competition, Artificial Intelligence for Cyber Security, Artificial Intelligence Safety, Dialog System Technology Challenge, Engineering Dependable and Secure Machine Learning Systems, Games and Simulations for Artificial Intelligence, Health Intelligence, Knowledge Extraction from Games, Network Interpretability for Deep Learning, Plan, Activity, and Intent Recognition, Reasoning and Learning for Human-Machine Dialogues, Reasoning for Complex Question Answering, Recommender Systems Meet Natural Language Processing, Reinforcement Learning in Games, and Reproducible AI. This report contains brief summaries of the all the workshops that were held.

scholarly journals CARPAL: Confidence-Aware Intent Recognition for Parallel Autonomy

2021 ◽  
pp. 1-1
Author(s):  
Xin Huang ◽  
Stephen Mcgill ◽  
Jonathan Decastro ◽  
Luke Fletcher ◽  
John Leonard ◽  
...  
Keyword(s):  
Intent Recognition

MyrrorBot : A Digital Assistant Based on Holistic User Models for Personalized Access to Online Services

2021 ◽  
Vol 39 (4) ◽  
pp. 1-34
Author(s):  
Cataldo Musto ◽  
Fedelucio Narducci ◽  
Marco Polignano ◽  
Marco De Gemmis ◽  
Pasquale Lops ◽  
...  
Keyword(s):  
Natural Language ◽  
Information Needs ◽  
Effective Interaction ◽  
Personal Digital Assistant ◽  
User Profiling ◽  
Online Services ◽  
Intent Recognition ◽  
User Models ◽  
Time Required ◽  
The Way

In this article, we present MyrrorBot , a personal digital assistant implementing a natural language interface that allows the users to: (i) access online services, such as music, video, news, and food recommendation s, in a personalized way, by exploiting a strategy for implicit user modeling called holistic user profiling ; (ii) query their own user models, to inspect the features encoded in their profiles and to increase their awareness of the personalization process. Basically, the system allows the users to formulate natural language requests related to their information needs. Such needs are roughly classified in two groups: quantified self-related needs (e.g., Did I sleep enough? Am I extrovert? ) and personalized access to online services (e.g., Play a song I like ). The intent recognition strategy implemented in the platform automatically identifies the intent expressed by the user and forwards the request to specific services and modules that generate an appropriate answer that fulfills the query. In the experimental evaluation, we evaluated both qualitative (users’ acceptance of the system, usability) as well as quantitative (time required to complete basic tasks, effectiveness of the personalization strategy) aspects of the system, and the results showed that MyrrorBot can improve the way people access online services and applications. This leads to a more effective interaction and paves the way for further development of our system.

scholarly journals A Computerized Text and Cluster Analysis Approach to Psychotherapy Talk

2020 ◽  
Vol 9 (1) ◽  
pp. 4-25
Author(s):  
Dennis Tay
Keyword(s):  
Cluster Analysis ◽  
Agglomerative Hierarchical Clustering ◽  
Analytic Thinking ◽  
Future Directions ◽  
Analysis Techniques ◽  
Entry Points ◽  
And Cluster Analysis ◽  
Language Styles ◽  
Computer Text ◽  
Qualitative Exploration

This paper illustrates an analytical approach combining LIWC, a computer text-analytic application, with cluster analysis techniques to explore ‘language styles’ in psychotherapy across sessions in time. It categorizes session transcripts into distinct clusters or styles based on linguistic (di)similarity and relates them to sessional progression, thus providing entry points for further qualitative exploration. In the first step, transcripts of four illustrative therapist-client dyads were scored under ten LIWC variables including ‘analytic thinking’, ‘clout’, ‘authenticity’, ‘emotional tone’, and pronoun types. In the next step, agglomerative hierarchical clustering uncovered distinct session clusters that are differently distributed in each dyad. The relationships between these clusters and the chronological progression of sessions were then further discussed in context as contrastive exemplars. Applications, limitations and future directions are highlighted.

A Vision-Based Architecture for Intent Recognition

2007 ◽  
pp. 173-182 ◽  
Author(s):  
Alireza Tavakkoli ◽  
Richard Kelley ◽  
Christopher King ◽  
Mircea Nicolescu ◽  
Monica Nicolescu ◽  
...  
Keyword(s):  
Intent Recognition
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