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Coreference resolution plays a significant role in natural language processing systems. It is the method of figuring out all the noun phrases that refer back to the identical real world entity. Several researches have been done in noun phrase coreference resolution by using certain machine learning techniques. Our paper proposes a machine learning approach using support vector machines (SVM) towards...
Long short-term memory (LSTM) is a significant approach to capture the long-range temporal context in sequences of arbitrary length. This had shown astonishing performance in sentence and document modeling. To leverage this, we use LSTM network to the encrypted text categorization at character and word level of texts. These texts are transformed in to dense word-vectors by using bag-of-words embedding...
Word sense disambiguation is the process of identifying existence of polysemous words in the text and disambiguating the appropriate sense satisfying the given context in Kannada language. The proposed methodology uses the synonyms of the target word and its surrounding words' gloss in combination with part of speech tagging to determine the overlap between the senses of the polysemous word or the...
Document summarization is a strategy, intended to extract information from multiple documents, deliberating the same subject. Many software applications handle document summarization, helping people grab the main thought, from a collection of documents, within a short time. Automatic summaries present information algorithmically extracted from multiple sources, without any impressionistic human intervention...
Paraphrase Detection is the task of examining if two sentences convey the same meaning or not. Here, in this paper, we have chosen a sentence embedding by unsupervised RAE vectors for capturing syntactic as well as semantic information. The RAEs learn features from the nodes of the parse tree and chunk information along with unsupervised word embedding. These learnt features are used for measuring...
The struggle of technology to understand natural language has been one of the greatest hurdles of humankind. Various techniques and algorithms have contributed to significant advancements in the field of NLP. One of the most primary challenges that NLP faces is being able to determine the meaning and essence of a sentence which may have multiple variations of syntax and semantics. Crossword solving...
Question Answering (QA) is the method of automatically answering a question asked by human in natural language using either a pre-structured database or a collection of documents. It is a rising new information service following the popularization of search engines. In this paper we introduce a graph-based QA system for reading comprehension tests that pick out the sentence in the passage that best...
News videos store a huge amount of information and are a source of historical archives. The amount of news data is growing rapidly and unpredictably, hence video indexing on news videos is a tedious job. Manual indexing even though effective, it is slow and most expensive for a massive volume of data. Content Based Indexing and Retrieval (CBIR) is a solution for this problem. Textual modality based...
The main goal of focused web crawlers is to retrieve as many relevant pages as possible. However, most of the crawlers use page rank algorithm to lineup the pages in the crawler frontier. Since the page rank algorithm suffers from the drawback of “Richer get rich phenomenon”, focused crawlers often fail to retrieve the hidden relevant pages. This paper presents a novel approach for retrieving the...
Easy access to high speed communication network and sharing of information via social media, has led to large amount of multimedia content seamlessly available to end user. Searching for similar images or video clips within a collection of videos is a common activity. This paper proposes a retrieval approach for similar video clip based on dense descriptor called serial walk local descriptor. The...
Chatbots are programs that mimic human conversation using Artificial Intelligence (AI). It is designed to be the ultimate virtual assistant, entertainment purpose, helping one to complete tasks ranging from answering questions, getting driving directions, turning up the thermostat in smart home, to playing one's favorite tunes etc. Chatbot has become more popular in business groups right now as they...
In Artificial Intelligence, games are the most challenging and exploited field. A language game is one such type of open-world game in which the word or phrase meaning plays an important role. Playing and solving such type of game is based on the player's ability to find the solution which depends on the richness of the player's cultural background for answering the question by understanding the question...
Abstractive multi-document summarization aims at generating new sentences whose elements originate from different source sentence. It can be achieved via phrase selection and merging approach which aims at constructing new sentences by exploring syntactic units such as fine-grained noun and verb phrase. It can be also achieved by extracting semantic information from source sentence which uses the...
Tagging provides a convenient means to assign tokens of identification to research papers which facilitate recommendation, search and disposition process of research papers. This paper contributes a document centered approach for auto-tagging of research papers. The auto-tagging method mainly comprises of two processes:- classification and tag selection. The classification process involves automatic...
With the rising trend in research and development of autonomous vehicles, it is important to keep in mind the cost effectiveness of the system. The cost of high-end sensor technologies being astronomically expensive, the research opportunities are restricted to a select few of high-tech companies and research laboratories such as Google, Tesla, Ford, and the likes of it. Hence our main focus is to...
The word ontology refers to the hierarchical structure of entities and their relationships. The entities are nodes and each node is dominated by their parent node in the hierarchical structure. The nodes are related by semantic and lexical relations such as synonymy, homonymy, meronymy, antonymy, etc. Hierarchical structure is created for different types of semantic domains. The top domains are entities,...
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