scholarly journals A Semantic Text Summarization Method using ontology based Knowledge

2020 ◽  
Vol 6 (11) ◽  
pp. 122-125
Author(s):  
Dr.A.Mekala
Keyword(s):  
Data Mining ◽  
Health Care ◽  
Information Source ◽  
Information Access ◽  
Text Summarization ◽  
Common Information ◽  
Related Information ◽  
Princeton University ◽  
Summarization Method ◽  
User Query

Data mining is a method which finds useful patterns from large amount of data. As vast amounts of information are created quickly, effective information access becomes an important matter. Particularly for important domains, such as health check and monetary areas, well-organized recovery of succinct and related information is highly desired. In this paper we propose a new user query based text summarization technique that makes use of WordNet, a common information source from Princeton University. Our summarization structure is expressly tuned to recapitulate health care documents.

PERSONALIZING THE SOURCE SELECTION AND THE RESULT MERGING PROCESS

2009 ◽  
Vol 18 (02) ◽  
pp. 331-354 ◽  
Author(s):  
SAMIR KECHID ◽  
HABIBA DRIAS
Keyword(s):  
Information Retrieval ◽  
Information Needs ◽  
Retrieval System ◽  
Information Source ◽  
Information Access ◽  
Information Retrieval System ◽  
Specific Information ◽  
Distributed Environment ◽  
Source Selection ◽  
User Query

The World Wide Web knows an incessant and very fast development. Currently, finding useful information on the Web is a time consuming process. In this paper, we present PIRS a personalized Information Retrieval System in a distributed environment. Most prior research in distributed information access focused on selecting and merging information that has the most relevant content according to the query but ignored the user's specific needs. The underlying idea is that different users have different backgrounds, goals and interests when seeking information and thus, the same query may cover different specific information needs according to who emitted it. However, with the ever expanding Web, users are faced with a huge number of information resources. Consequently, such query-based information access strategies lead to inaccurate query results. PIRS extends the state of the art in a Web-based information retrieval system in distributed environment. First, it develops models for representing both user and information source using feature based profiles. Second, PIRS expands a user query according to his profile. Third, it develops algorithms for source selection and results merging that personalize the computation of the relevance score of a document in response to the user's query. PIRS has been experimented with several known information source. The experimental results obtained show the effectiveness of our approach.

An Automatic Text Summarization Method with the Concern of Covering Complete Formation

2020 ◽  
Vol 13 (5) ◽  
pp. 977-986
Author(s):  
Srinivasa Rao Kongara ◽  
Dasika Sree Rama Chandra Murthy ◽  
Gangadhara Rao Kancherla
Keyword(s):  
Research Method ◽  
Research Work ◽  
Fuzzy Rule ◽  
Text Summarization ◽  
Document Summarization ◽  
Summarization Method ◽  
Overall Evaluation ◽  
Multiple Documents ◽  
Rule System ◽  
Value Decomposition

Background: Text summarization is the process of generating a short description of the entire document which is more difficult to read. This method provides a convenient way of extracting the most useful information and a short summary of the documents. In the existing research work, this is focused by introducing the Fuzzy Rule-based Automated Summarization Method (FRASM). Existing work tends to have various limitations which might limit its applicability to the various real-world applications. The existing method is only suitable for the single document summarization where various applications such as research industries tend to summarize information from multiple documents. Methods: This paper proposed Multi-document Automated Summarization Method (MDASM) to introduce the summarization framework which would result in the accurate summarized outcome from the multiple documents. In this work, multi-document summarization is performed whereas in the existing system only single document summarization was performed. Initially document clustering is performed using modified k means cluster algorithm to group the similar kind of documents that provides the same meaning. This is identified by measuring the frequent term measurement. After clustering, pre-processing is performed by introducing the Hybrid TF-IDF and Singular value decomposition technique which would eliminate the irrelevant content and would result in the required content. Then sentence measurement is one by introducing the additional metrics namely Title measurement in addition to the existing work metrics to accurately retrieve the sentences with more similarity. Finally, a fuzzy rule system is applied to perform text summarization. Results: The overall evaluation of the research work is conducted in the MatLab simulation environment from which it is proved that the proposed research method ensures the optimal outcome than the existing research method in terms of accurate summarization. MDASM produces 89.28% increased accuracy, 89.28% increased precision, 89.36% increased recall value and 70% increased the f-measure value which performs better than FRASM. Conclusion: The summarization processes carried out in this work provides the accurate summarized outcome.

Designing a Chat-Bot for College Information using Information Retrieval and Automatic Text Summarization Techniques

2020 ◽  
Vol 01 ◽  
Author(s):  
Radha Guha
Keyword(s):  
Information Retrieval ◽  
Language Processing ◽  
Latent Dirichlet Allocation ◽  
Semantic Analysis ◽  
Text Summarization ◽  
The Internet ◽  
Specific Domain ◽  
User Query ◽  
College Information ◽  
Chat Bot

Background:: In the era of information overload it is very difficult for a human reader to make sense of the vast information available in the internet quickly. Even for a specific domain like college or university website it may be difficult for a user to browse through all the links to get the relevant answers quickly. Objective:: In this scenario, design of a chat-bot which can answer questions related to college information and compare between colleges will be very useful and novel. Methods:: In this paper a novel conversational interface chat-bot application with information retrieval and text summariza-tion skill is designed and implemented. Firstly this chat-bot has a simple dialog skill when it can understand the user query intent, it responds from the stored collection of answers. Secondly for unknown queries, this chat-bot can search the internet and then perform text summarization using advanced techniques of natural language processing (NLP) and text mining (TM). Results:: The advancement of NLP capability of information retrieval and text summarization using machine learning tech-niques of Latent Semantic Analysis(LSI), Latent Dirichlet Allocation (LDA), Word2Vec, Global Vector (GloVe) and Tex-tRank are reviewed and compared in this paper first before implementing them for the chat-bot design. This chat-bot im-proves user experience tremendously by getting answers to specific queries concisely which takes less time than to read the entire document. Students, parents and faculty can get the answers for variety of information like admission criteria, fees, course offerings, notice board, attendance, grades, placements, faculty profile, research papers and patents etc. more effi-ciently. Conclusion:: The purpose of this paper was to follow the advancement in NLP technologies and implement them in a novel application.

scholarly journals “I actually got my first job through my ex-colleague”: Employment-related information seeking behavior of Bangladeshi immigrants in Canada

2021 ◽  
pp. 096100062199280
Author(s):  
Nafiz Zaman Shuva
Keyword(s):  
Information Seeking ◽  
Information Needs ◽  
Information Sources ◽  
Information Source ◽  
Occupational Status ◽  
Structured Interviews ◽  
Related Information ◽  
Immigrant Professionals ◽  
Government Of Canada ◽  
First Job

This study explores the employment-related information seeking behaviour of Bangladeshi immigrants in Canada. Using a mixed-methods approach, the study conducted semi-structured interviews with 60 Bangladeshi immigrants in Ontario, Canada, and obtained 205 survey responses. The study highlights the centrality of employment-related settlement among Bangladeshi immigrants in Ontario and reports many immigrants not being able to utilize their education and skills after arrival in Canada. The results show that Bangladeshi immigrants utilize various information sources for their employment in Canada, including friends and professional colleagues, online searchers, and settlement agencies. Although Bangladeshi immigrants utilized a large array of information sources for meeting their employment-related information needs, many interview participants emphasized that the employment-related benefits they received was because of their access to friends and professional colleagues in Canada. The survey results echoed the interview findings. The cross-tabulation results on post-arrival information sources and occupation status as well as first job information sources and occupational status in Canada show a significant association among the use of the information source “friends and professional colleagues in Canada” and immigrants’ occupational status. The study highlights the benefits of professional colleagues among immigrants in employment-related settlement contexts. It also reports the challenges faced by many immigrant professionals related to employment-related settlement because of the lack of access to their professional friends and colleagues in Canada. The author urges the Federal Government of Canada, provincial governments, and settlement agencies working with newcomers to offer services that would connect highly skilled immigrants with their professional networks in Canada, in order to get proper guidance related to obtaining a professional job or alternative career. The author calls for further studies on employment-related information seeking by immigrants to better understand the role information plays in their settlement in a new country.

Health information needs, sources, and barriers of primary care patients to achieve patient-centered care: A literature review

2016 ◽  
Vol 22 (4) ◽  
pp. 992-1016 ◽  
Author(s):  
Martina A Clarke ◽  
Joi L Moore ◽  
Linsey M Steege ◽  
Richelle J Koopman ◽  
Jeffery L Belden ◽  
...  
Keyword(s):  
Primary Care ◽  
Health Information ◽  
Information Search ◽  
Information Needs ◽  
Information Sources ◽  
Medical Condition ◽  
Information Access ◽  
The Internet ◽  
Common Information ◽  
Primary Care Patients

To synthesize findings from previous studies assessing information needs of primary care patients on the Internet and other information sources in a primary care setting. A systematic review of studies was conducted with a comprehensive search in multiple databases including OVID MEDLINE, CINAHL, and Scopus. The most common information needs among patients were information about an illness or medical condition and treatment methods, while the most common information sources were the Internet and patients’ physicians. Overall, patients tend to prefer the Internet for the ease of access to information, while they trust their physicians more for their clinical expertise and experience. Barriers to information access via the Internet include the following: socio-demographic variables such as age, ethnicity, income, education, and occupation; information search skills; and reliability of health information. Conclusion: Further research is warranted to assess how to create accurate and reliable health information sources for both Internet and non-Internet users.

Challenges of Providing Health Care in Complex Emergencies: A Systematic Review

2021 ◽  
pp. 1-5
Author(s):  
Hesam Seyedin ◽  
Morteza Rostamian ◽  
Fahimeh Barghi Shirazi ◽  
Haleh Adibi Larijani
Keyword(s):  
Systematic Review ◽  
Health Care ◽  
Health Services ◽  
Health Care Providers ◽  
Health Care Delivery ◽  
Qualitative Content Analysis ◽  
Care Delivery ◽  
Information Access ◽  
Care Providers ◽  
Complex Emergencies

Abstract Providing health care in times of complex emergencies (CEs) is one of the most vital needs of people. CEs are situations in which a large part of the population is affected by social unrest, wars, and food shortages. This systematic review study was conducted to identify the challenges of health-care delivery in CEs. We searched terms related to health-care delivery and CEs in PubMed, Web of Sciences, Science Direct, and Google scholar databases, as well as Persian databases SID and Magiran. The searching keywords included: “Health Care, Complex Crises, War, Humanitarian, Refugees, Displaced Persons, Health Services, and Challenges.” Of 409 records, we selected 6 articles based on the Preferred Reporting Items for Systematic Reviews (PRISMA) checklist. Studies were analyzed through qualitative content analysis. The results show that CEs affect health-care delivery in 4 primary areas: the workforce, infrastructure, information access, and organization of health services. These areas can pose potential threats for health-care providers and planners at times of emergencies. Thus, they should be informed about these challenges to strengthen the health-care system.

scholarly journals THE ROLE OF HEALTH INFORMATION SYSTEM IN MATERNAL AND CHILD HEALTHCARE SERVICES

2017 ◽  
Vol 10 (6) ◽  
pp. 29
Author(s):  
Rakhi Chowdhury ◽  
Leena Kumari ◽  
Subhamay Panda
Keyword(s):  
Health Care ◽  
Information System ◽  
Child Health ◽  
Health Information ◽  
Maternal And Child Health ◽  
Health Information System ◽  
Health Care Sector ◽  
Related Information ◽  
Health Related ◽  
And Child Health

Health information system deals with any system that helps in capturing, storing, transmitting, and managing health-related information of an individual or to demonstrate the activities or organizations working within health-care sector. In the developing countries, maternal and child health is gaining concern due to increasing cases of morbidity and mortality. The disparities among the maternal, infant, and child health are a growing concern in India and are governed by various determinants such as socioeconomic status, literacy, quality of health care, discrimination, and biological and genetic factors. Accurate and reliable health information and data are the basis for decision-making across the health-care sector and are crucial for the development and implementation of health system policy by the policy-makers. Strict monitoring and evaluation of the present program design and its implementation is required at the microlevel to effectively utilize the resources for the improvement of maternal and child health. Our present article focuses on evaluating the coverage gap at the different levels for the provision of health-care facilities to maternal, neonatal, and child health, immunization, and treatment of poor children. Big data plays a major role in providing sound and reliable health-related information and also help in managing and recording structured and unstructured data. More concrete plans are required further to reduce the inequalities in health-care interventions for providing better maternal and child health-care services in our nation.

scholarly journals PENGEMBANGAN INTELLIGENT DATA COLLECTOR UNTUK ANALISIS BIG DATA ARTIKEL BERITA ONLINE

2018 ◽  
Vol 3 (1) ◽  
pp. 49-59
Author(s):  
Zul Indra ◽  
Liza Trisnawati
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Sentiment Analysis ◽  
Opinion Mining ◽  
Text Summarization ◽  
Data Collector

Big data  telah menjadi salah satu topik yg paling menarik dalam dunia teknologi informasi sekarang ini. Salah satu sumber big data yang tersedia dan bebas diakses adalah artikel berita online. Dalam sehari, sebuah situs berita populer bisa menghasilkan lebih dari 100 artikel berita baru. Bayangkan berapa banyak jumlah halaman berita yang tersedia untuk kita baca sekarang ini. Sementara itu, tahap awal untuk melakukan analisis big data terhadap artikel berita online adalah data storing dan preprocessing. Berdasarkan pemikiran tersebut maka perlu dikembangkan suatu aplikasi yang bisa mengumpulkan artikel berita online secara otomatis untuk kemudian di analisis lebih lanjut. Penelitian ini bermaksud mengembangkan suatu aplikasi yang diberi nama dengan intelligent data collector (IDC) yang memudahkan kita untuk mengumpulkan artikel berita online. Aplikasi IDC ini mengumpulkan artikel berita online kemudian melakukan preprocessing terhadap artikel-artikel tersebut dan menyimpannya dalam database lokal. Database ini kemudian bisa digunakan lebih lanjut untuk berrbagai macam data mining proses seperti opinion mining (sentiment analysis), topic classification, text summarization dan lain sebagainya.

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