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The present work proposes an unsupervised approach for recognising relations between named entities from a large corpora based on crime in Indian states and union territories. Initially, named entities have been identified from the extracted crime corpus and certain pair of entities have been chosen that facilitates the crime analysis. Then the entity pairs with their intermediate context words have...
Understanding user query intent is a crucial task to Question-Answering area. With the development of online health services, online health communities generate huge amount of valuable medical Question-Answering data, where user intention can be mined. However, the queries posted by common users have many domain concepts and colloquial expressions, which make the understanding of user intents very...
Natural language processing methods are widely used to study the relationship between traditional Chinese medicine (TCM) prescriptions and diseases in textual data, and the results can discover the essence of TCM literature. In this paper, we get TCM treatment information from the abstract text at first by using the web crawlers. Second, the eigenvectors will be selected from the cleaned abstract...
Unstructured document and archive stacks that are formed in the past years are growing in size faster these days and they need to be clarified with various methods. This increases the interest in natural language processing discipline day by day and makes it more popular. In this study, we've tried to calculate the similarities between document stacks, that no information is presented onbehalf of...
Streaming information flow allows identification of linguistic similarities between language pairs in real time as it relies on pattern recognition of grammar rules, semantics and pronunciation especially when analyzing so called international terms, syntax of the language family as well as tenses transitivity between the languages. Overall, it provides a backbone translation knowledge for building...
The need of smart information retrieval systems is in contrast with the difficulties to deal with huge amount of data. In this paper we present a Big Data Analytics architecture used to implement a semantic similarity search tool for natural language texts in biomedical domain. The implemented methodology is based on Word Embeddings (WEs) models obtained using the word2vec algorithm. The system has...
The majority of clinical data is only available in unstructured text documents. Thus, their automated usage in data-based clinical application scenarios, like quality assurance and clinical decision support by treatment suggestions, is hindered because it requires high manual annotation efforts. In this work, we introduce a system for the automated processing of clinical reports of mamma carcinoma...
With the rapid growth of service volumes and types, discovering services in an efficient and accurate manner has become a significant challenge in service computing. Service clustering is an important technology to improve the efficiency of service discovery. In this paper, we propose a new service clustering approach, which starts from service documents and is based on the functional semantics of...
The goal of medical concept extraction is to identify phrases that refer to medical concepts of interest such as problems, treatments and tests from medical documents. In this study, three types of medical concept extraction models are developed and then compared them. The first concept extraction task is mainly based upon semantic features obtained from a domain-knowledge based method using MetaMap,...
During the last decade the amount of scientific information available on-line increased at an unprecedented rate and this situation is unlikely to change. As a consequence, nowadays researchers are overwhelmed by an enormous and continuously growing number of publications to consider when they perform research activities like the exploration of advances in specific topics, peer reviewing, writing...
One of the greatest challenges of an enterprise's service center is to ensure that their engineers and customers are provided with the right information in a timely fashion. For this purpose, modern organizations operate a wide range of information support systems to assist customers with critical service requests and to provide proactive monitoring, where possible, to prevent service requests from...
This paper proposes a new keyword extraction method that uses bag-of-concept to extract keywords from Arabic text. The proposed algorithm utilizes semantic vector space model instead of traditional vector space model to group words into classes. The new method built word-context matrix where the synonym words will be grouped into the same class. The evaluation of new approach was conducted using dataset...
Sentiment Analysis is the process which helps to identify and classifying the opinions or feelings expressed in opinioned data, in order to ascertain whether the attitude of the writer towards a particular service, product etc. is negative, positive or neutral. Sentiment analysis also helps the consumers to identify if the information in the neighborhood of the product or service is satisfactory or...
Modern databases contain an enormous amount of information stored in a structured format. This information is processed to acquire knowledge. However, the process of information extraction from a Database System is cumbersome for non-expert users as it requires an extensive knowledge of DBMS languages. Therefore, an inevitable need arises to bridge the gap between user requirements and the provision...
Aiming at the problem that the traditional single neural network method is limited in feature dimension extraction, a new deep-fusion convolutional neural network is proposed. It uses two kinds of different representations (i.e., word vector and shortest dependency path) as different inputs of convolutional neural network, therefore, it is capable to learn more dimension text features automatically...
In recent years patents have become increasingly important for businesses to protect their intellectual capital and as a valuable source of information. Patent information is, however, not employed to its full potential and the interpretation of structured and unstructured patent information in large volumes remains a challenge. We address this by proposing an integrated interdisciplinary approach...
Aspect Based Sentiment Analysis (ABSA) provides further insight into the analysis of social media. Understanding user opinion about different aspects of products, services or policies can be used for improving and innovating in an effective way. Thus, it is becoming an increasingly important task in the Natural Language Processing (NLP) realm. The standard pipeline of aspect-based sentiment analysis...
The problem being addressed in this paper is that using brute force in Natural Language Processing and Machine Learning combined with advanced statistics will only approximate meaning and thus will not deliver in terms of real text understanding. Counting words and tracking word order or parsing by syntax will also result in probability and guesswork at best. Their vendors struggle in delivering accurate...
While several relation extraction algorithms have been developed in the past decade, mainly in the English language, only few researchers target the Arabic language owing to its complexity and rich morphology. This paper proposes a semi-supervised pattern-based bootstrapping technique to extract Arabic semantic relation that lies between entities. In order to enhance the performance to suit the morphologically...
Concept maps are resources for the representation and construction of knowledge. They allow the showing, through concepts and relationships, how knowledge about a subject is organized. Technological advances have boosted the development of technological approaches that help the automatic construction of a map, in order to facilitate and provide the benefits of that resource more broadly. Because of...
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