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Action Rules are vital data mining method for gaining actionable knowledge from the datasets. Meta actions are the sub-actions to the Action Rules, which intends to change the attribute value of an object, under consideration, to attain the desirable value. The essence of this paper to propose a new optimized and more promising system, in terms of speed and efficiency, for generating meta-actions...
Improving and assessing knowledge on a topic is need of the current generation. In the traditional system, experts create assessments manually by reading articles and generating questions on a topic. However, it is very effort and time consuming to read and create questions for every article. Therefore, learners find it difficult to assess their knowledge on a topic owing to no- or low-availability...
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...
A significant part of our knowledge is relationships between two terms. However, most of these information is documented as unstructured text in various forms, like books, online articles and webpages. Extract those information and store them in a structured database could help people utilize these information more conveniently. In this study, we proposed a novel approach to extract the relationships...
The widespread prevalence of dietary supplements has drawn extensive attention due to the safety and efficacy issue. Clinical notes document a great amount of detailed information on dietary supplement usage, thus providing a rich source for clinical research on supplement safety surveillance. Identification the use status of dietary supplements is one of the initial steps for the ultimate goal of...
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...
The unstructured data, which volume grows exponentially, often hide important and even vital information for society and companies. It takes a lot of work to extract information such as the nature of consumption in a category of individuals, trends, etc. When it comes to statistical data, it is often very useful to synthesize this kind of information in the form of graphical representations. In this...
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...
Shifts in technology can bring dramatic changes in the competitive positioning of an organization. On the one hand it provides opportunities to create new value propositions and thus opportunity to grow, but on the other hand it also threatens the existence of organizations that fail to grasp the scale and/or significance of given technological change. Technology intelligence and forecasting have...
Intrauterine devices (IUDs) are highly-effective contraceptive methods for preventing unintended pregnancy and related adverse outcomes. Clinical Decision Support (CDS) systems could aid care providers in identifying patients at risk for pregnancy due to lack of contraceptive use. However, research suggests that this information is not reliably documented in structured data fields for query, but rather...
The authors discuss the problem of distributed knowledge acquisition for the construction of complete and consistent knowledge bases in integrated expert systems, in particular dynamic integrated expert systems, via sharing of knowledge sources of different topologies (databases as electronic media, experts and problem-oriented texts). This work is focused on models and methods of distributed knowledge...
Recent years have witnessed web services drastically becoming popular in our daily lives, and many consumers take user reviews of products into account when planning purchases. The number of cosmetic review sites, users, and products posted have been increasing year by year. For example, when a user searches for skin lotions using the @cosme website, she consults with reviews of users with similar...
People tend to read multiple news articles on a topic since a single article may not contain all important information. A summary of all the articles related to topic will save the time and energy. Text Summarization is a way of minimizing a textual document to a meaningful summary. In this research, an extractive-based approach is used to generate a two-level summary from online news articles. News...
We describe efforts to bring new methods of search analytics, machine learning, natural language processing and data visualization to address the challenge of finding and extracting meaning from unstructured text and multimedia content. We use the Polar domain to motivate the problem and our proposed solution. However our techniques are applicable and scalable to other domains.
Anonymous social network has attracted everincreasing attention from research community in recent years, however, it also brings some complications to ours daily life. We want to provide a reference for further regulation by addressing the problems in anonymous social network ecology. In this paper we focus our attention on summarizing the ecological status of anonymous social networks in a complete...
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...
Clinical summarization means the collection and synthesis of a patient's significant data, undertaken in order to support health-care providers in the process of patient care. Considering that medical information comes from multiple sources, a system for the automatic generation of problem lists could prove to be very effective in terms of saving time in the analysis of large amounts of medical data...
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...
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