A Survey on Chatbot: Futuristic Conversational Agent for User Interaction

Author(s):  
Parth Goel ◽  
Amit Ganatra
2017 ◽  
pp. 030-050
Author(s):  
J.V. Rogushina ◽  

Problems associated with the improve ment of information retrieval for open environment are considered and the need for it’s semantization is grounded. Thecurrent state and prospects of development of semantic search engines that are focused on the Web information resources processing are analysed, the criteria for the classification of such systems are reviewed. In this analysis the significant attention is paid to the semantic search use of ontologies that contain knowledge about the subject area and the search users. The sources of ontological knowledge and methods of their processing for the improvement of the search procedures are considered. Examples of semantic search systems that use structured query languages (eg, SPARQL), lists of keywords and queries in natural language are proposed. Such criteria for the classification of semantic search engines like architecture, coupling, transparency, user context, modification requests, ontology structure, etc. are considered. Different ways of support of semantic and otology based modification of user queries that improve the completeness and accuracy of the search are analyzed. On base of analysis of the properties of existing semantic search engines in terms of these criteria, the areas for further improvement of these systems are selected: the development of metasearch systems, semantic modification of user requests, the determination of an user-acceptable transparency level of the search procedures, flexibility of domain knowledge management tools, increasing productivity and scalability. In addition, the development of means of semantic Web search needs in use of some external knowledge base which contains knowledge about the domain of user information needs, and in providing the users with the ability to independent selection of knowledge that is used in the search process. There is necessary to take into account the history of user interaction with the retrieval system and the search context for personalization of the query results and their ordering in accordance with the user information needs. All these aspects were taken into account in the design and implementation of semantic search engine "MAIPS" that is based on an ontological model of users and resources cooperation into the Web.


Author(s):  
Goh Eg Su ◽  
◽  
Mohd Sharizal Sunar ◽  
Rino Andias ◽  
Ajune Wanis Ismail ◽  
...  

1999 ◽  
Vol 39 (4) ◽  
pp. 193-201
Author(s):  
P. J. A. Gijsbers

The need for integrated analysis poses a request for integration of computer models, paying extra attention to interfaces, data management and user interaction. Sector wide standardization using data dictionaries and data exchange formats can be a great help in streamlining data exchange. However, this type of standardization can have some drawbacks for a generic framework for model integration. Another concept, called Model Data Dictionary (MDD), has been developed as an alternative for proper data management. The concept is a variant on the federated database concept, a concept where local databases maintain their autonomy, while an interconnection database provides a link for sharing data. The MDD is based on a highly generic data model for geographic referenced objects, which if needed facilitates mapping of the sector wide data dictionary. External interfaces provide, in combination with a data format mapping component, a link to SQL-based data sources and model specific databases. A generic Object Data Editor (ODE), linked to the MDD, has been proposed for provision of a common data editing facility for mathematical models. A test version of the combined MDD/ODE-concept has shown the applicability for integration of all kinds of geographic object oriented mathematical models (both simulation and optimization).


Iproceedings ◽  
2016 ◽  
Vol 2 (1) ◽  
pp. e27 ◽  
Author(s):  
Lazlo Ring ◽  
Timothy Bickmore ◽  
Paola Pedrelli

2021 ◽  
Vol 11 (11) ◽  
pp. 4834
Author(s):  
Kai Ren Teo ◽  
Balamurali B T ◽  
Jianying Zhou ◽  
Jer-Ming Chen

Many mobile electronics devices, including smartphones and tablets, require the user to interact physically with the device via tapping the touchscreen. Conveniently, these compact devices are also equipped with high-precision transducers such as accelerometers and microphones, integrated mechanically and designed on-board to support a range of user functionalities. However, unintended access to these transducer signals (bypassing normal on-board data access controls) may allow sensitive user interaction information to be detected and thereby exploited. In this study, we show that acoustic features extracted from the on-board microphone signals, supported with accelerometer and gyroscope signals, may be used together with machine learning techniques to successfully determine the user’s touch input location on a touchscreen: our ensemble model, namely the random forest model, predicts touch input location with up to 86% accuracy in a realistic scenario. Accordingly, we present the approach and techniques used, the performance of the model developed, and also discuss limitations and possible mitigation methods to thwart possible exploitation of such unintended signal channels.


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