Natural language processing is the study of mathematical and computational modelling of various a... more Natural language processing is the study of mathematical and computational modelling of various aspects of language and the improvement of a wide range of systems. Natural language is any language that arises as an innate facility for language possessed by the human intellect; it may be spoken, signed or written. Machine learning algorithms are used in conjunction with language models to recognize text in natural language processing systems, which may also employ speech models and hardware/software specialized to process and recognize speech or even signed (gesture-based) language. Natural language processing provides a potential means of gaining access to the information inherent in the large amount of text made available through the internet. This paper presents the basic concepts of Natural Language Processing, levels of linguistic analysis, Parsing techniques, Semantic analysis and applications of natural language in real-world.
Sentiment analysis and opinion mining is the field of study that analyzes people’s opinions, sent... more Sentiment analysis and opinion mining is the field of study that analyzes people’s opinions, sentiments, evaluations, attitudes, and emotions from written language. It is one of the most active research areas in natural language processing and is also widely studied in data mining, web mining, and text mining. Sentiment analysis has been used in several applications including analysis of the repercussions of events in social networks, analysis of opinions about products and services. The growing importance of sentiment analysis coincides with the growth of social media such as reviews, forum discussions, blogs, micro-blogs, Twitter, and social networks. Methods like supervised machine learning and lexical-based approaches are available for measuring sentiments that have a huge volume of opinionated data recorded in digital form for analysis.
NLP and ontology based clustering — An integrated approach for optimal information extraction from social web
Social Web is a heterogeneous collection of both structured and unstructured dataprimarily compos... more Social Web is a heterogeneous collection of both structured and unstructured dataprimarily composed of contents from various social networking sites, blogs, online shopping sites and much more. The knowledge extracted from such data can be valuable for accuracy of search results in light of present explosion of information exchange over social web. The extraction of information patterns from unstructured data sets available at social networking sites viz. facebook, twitter, linkedin is a challenging task as it cannot be understood by machine to robotically process the data. Also, the major data source in the form of naive users triggers the significance of filtration of the relevant results. For effectual analysis of social web contents, this paper proposes integrated NLP and ontology based clustering TVC algorithm that generates semantically meaningful concepts from the social web content. The algorithm promises to optimize the web search results and to provide accuracy in searchin...
Semantic web represents a potential technology for realizing e-Learning requirements. Research wo... more Semantic web represents a potential technology for realizing e-Learning requirements. Research works in the field of e-Learning are represented by a wide range of applications, ranged from virtual classrooms to remote courses or distance learning. However, studies show that still it demands more effective approach. Semantic web has played an important role in designing such applications by either extending already existing applications to semantic web or creating new applications that are completely semantic web based. Use of semantic web techniques is a step further towards increasing the efficiency of applications by providing s of the knowledge as these are more effective in expressing an idea. Semantic Web enhances the capability of the semantic Web technology to access and process data from websites, databases, XML documents, and other systems to increase the amount of useful data retrieved exponentially. During the last few years semantic web has achieved long milestones and a...
Ontology Equipped Natural Language Processing for Real World Applications
Natural language processing is an area of artificial intelligence that defines a set of methods a... more Natural language processing is an area of artificial intelligence that defines a set of methods and techniques used to automate the translation process between computers and humans or mediate the human-machine communication. NLP focuses on developing systems that allow computers to communicate with people using everyday language and also concerns how computational methods can aid the understanding of human language. To make this possible, NLP has to define a communication format and software able to analyze, understand and give appropriate response. For the communication level, a formal representation of the knowledge is needed that can be represented by ontology. Ontology represents knowledge in a formal model based on conceptualization. This paper has threefold objective. Firstly, it defines ontology as a concept based model to represent objects, concepts, entities and relations that exist between objects. Users’ access to information and the presentation of information to users a...
13 Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. Abstract—Sem... more 13 Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. Abstract—Semantic web, next generation intelligent web, is one of the emerging research areas in intelligent web technology and has high potential for research. It can be considered as a content-aware intelligent web. SW technologies will influence the next generation of e-learning systems and applications. To structure the learning material, ontology is a key constituent in the structural design of the Semantic Web. Ontology is a formal specification of a particular domain that describes set of objects, properties that objects can have and various ways how these objects are related to each other.This paper has threefold objective. Firstly, it would help to understand Semantic Web currently exists as a vision, is a promising technology for realizing eLearning requirements. Ontology is primary and most important part of semantic web, improves the learning process as it focuses on relationship rather ...
Natural language processing is the study of mathematical and computational modelling of various a... more Natural language processing is the study of mathematical and computational modelling of various aspects of language and the improvement of a wide range of systems. Natural language is any language that arises as an innate facility for language possessed by the human intellect; it may be spoken, signed or written. Machine learning algorithms are used in conjunction with language models to recognize text in natural language processing systems, which may also employ speech models and hardware/software specialized to process and recognize speech or even signed (gesture-based) language. Natural language processing provides a potential means of gaining access to the information inherent in the large amount of text made available through the internet. This paper presents the basic concepts of Natural Language Processing, levels of linguistic analysis, Parsing techniques, Semantic analysis and applications of natural language in real-world.
Sentiment analysis and opinion mining is the field of study that analyzes people’s opinions, sent... more Sentiment analysis and opinion mining is the field of study that analyzes people’s opinions, sentiments, evaluations, attitudes, and emotions from written language. It is one of the most active research areas in natural language processing and is also widely studied in data mining, web mining, and text mining. Sentiment analysis has been used in several applications including analysis of the repercussions of events in social networks, analysis of opinions about products and services. The growing importance of sentiment analysis coincides with the growth of social media such as reviews, forum discussions, blogs, micro-blogs, Twitter, and social networks. Methods like supervised machine learning and lexical-based approaches are available for measuring sentiments that have a huge volume of opinionated data recorded in digital form for analysis.
NLP and ontology based clustering — An integrated approach for optimal information extraction from social web
Social Web is a heterogeneous collection of both structured and unstructured dataprimarily compos... more Social Web is a heterogeneous collection of both structured and unstructured dataprimarily composed of contents from various social networking sites, blogs, online shopping sites and much more. The knowledge extracted from such data can be valuable for accuracy of search results in light of present explosion of information exchange over social web. The extraction of information patterns from unstructured data sets available at social networking sites viz. facebook, twitter, linkedin is a challenging task as it cannot be understood by machine to robotically process the data. Also, the major data source in the form of naive users triggers the significance of filtration of the relevant results. For effectual analysis of social web contents, this paper proposes integrated NLP and ontology based clustering TVC algorithm that generates semantically meaningful concepts from the social web content. The algorithm promises to optimize the web search results and to provide accuracy in searchin...
Semantic web represents a potential technology for realizing e-Learning requirements. Research wo... more Semantic web represents a potential technology for realizing e-Learning requirements. Research works in the field of e-Learning are represented by a wide range of applications, ranged from virtual classrooms to remote courses or distance learning. However, studies show that still it demands more effective approach. Semantic web has played an important role in designing such applications by either extending already existing applications to semantic web or creating new applications that are completely semantic web based. Use of semantic web techniques is a step further towards increasing the efficiency of applications by providing s of the knowledge as these are more effective in expressing an idea. Semantic Web enhances the capability of the semantic Web technology to access and process data from websites, databases, XML documents, and other systems to increase the amount of useful data retrieved exponentially. During the last few years semantic web has achieved long milestones and a...
Ontology Equipped Natural Language Processing for Real World Applications
Natural language processing is an area of artificial intelligence that defines a set of methods a... more Natural language processing is an area of artificial intelligence that defines a set of methods and techniques used to automate the translation process between computers and humans or mediate the human-machine communication. NLP focuses on developing systems that allow computers to communicate with people using everyday language and also concerns how computational methods can aid the understanding of human language. To make this possible, NLP has to define a communication format and software able to analyze, understand and give appropriate response. For the communication level, a formal representation of the knowledge is needed that can be represented by ontology. Ontology represents knowledge in a formal model based on conceptualization. This paper has threefold objective. Firstly, it defines ontology as a concept based model to represent objects, concepts, entities and relations that exist between objects. Users’ access to information and the presentation of information to users a...
13 Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. Abstract—Sem... more 13 Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. Abstract—Semantic web, next generation intelligent web, is one of the emerging research areas in intelligent web technology and has high potential for research. It can be considered as a content-aware intelligent web. SW technologies will influence the next generation of e-learning systems and applications. To structure the learning material, ontology is a key constituent in the structural design of the Semantic Web. Ontology is a formal specification of a particular domain that describes set of objects, properties that objects can have and various ways how these objects are related to each other.This paper has threefold objective. Firstly, it would help to understand Semantic Web currently exists as a vision, is a promising technology for realizing eLearning requirements. Ontology is primary and most important part of semantic web, improves the learning process as it focuses on relationship rather ...
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