Personalized Content Extraction and Text Classification Using Effective Web Scraping Techniques

Karthikeyan, T.; Sekaran, K. Chandra; Ranjith, D.; Kumar, V. Vinoth; Balajee, J M

doi:10.4018/ijwp.2019070103

Cited by 69 publications

(25 citation statements)

References 17 publications

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“…By applying data scraping methods (Karthikeyan, Sekaran, Ranjith, & Balajee, 2019), the authors of the article created a unique tool of article collection by using R language. Articles were collected from the news portals by using keywords 'Visaginas city,' 'Ignalina NPP,' 'Astravyets NPP,' 'Chernobyl.'…”

Section: Methodsmentioning

confidence: 99%

Framing Nuclearity: Online Media Discourses in Lithuania

Mažeikienė

Kasperiūnienė

Tandžegolskienė

2021

MaC

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This article refers to the concept of nuclearity as a broader technopolitical phenomenon that implies a political and cultural configuration of technical and scientific matters. The nuclear media discourses become a site of tensions, struggles, and power relations between various institutions, social groups, and agents who seek to frame nuclear issues. The Bourdieusian concept of a field as a domain of social interaction is employed by the authors of this article seeking to reveal interactions and power configurations within and between several fields: journalism and media, economy, politics, and cultural production fields (cinematography, literature, and art). Commercial and political pressures on media raise a question about the autonomy of this field. Media coverage of nuclear issues in Lithuania during the period 2018–2020, includes media framing produced by different sponsors of the nuclear media discourses and agents from the above-mentioned fields of journalism, nuclear industry, politics, cinematography or arts. The media coverage includes the news and press releases produced within PR and public communication of the atomic energy industry by representing the decommissioning of the Ignalina Nuclear Power Plant, articles written by journalists about the atomic city Visaginas, and challenges faced by the local community due to the closure of the Ignalina Nuclear Power Plant. The nuclear discourse includes debates by politicians around the topic of the lack of safety of the construction of the Astravyets Nuclear Power Plant in Belarus, and media coverage of the HBO series <em>Chernobyl</em> representing a strong antinuclear narrative by portraying the Chernobyl disaster crisis and expressing strong criticism of communism. The authors of this article carried out a qualitative content analysis of media coverage on nuclear issues and revealed features of the discourse: interpretative packages, frames, framing devices (Gamson & Modigliani, 1989), and dominating actors and institutions supporting the discourse.

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Section: Methodsmentioning

confidence: 99%

Framing Nuclearity: Online Media Discourses in Lithuania

Mažeikienė

Kasperiūnienė

Tandžegolskienė

2021

MaC

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“…Web Scraping adalah teknik untuk mengekstrak informasi dari berbagai dokumen web secara otomatis. Web Scraping mengambil konten terkait berdasarkan kueri, menggabungkan dan mengubah data dari format tidak terstruktur menjadi representasi terstruktur (Karthikeyan et al, 2019). Framework TI yang diambil meliputi: ITIL, ISO 27001, dan COBIT yang diklasifikasikan menjadi title dan keyword pada tiap framework.…”

Section: Hasil Dan Pembahasan Hasil Pengumpulan Dataunclassified

Tren Penggunaan Framework COBIT, ITIL, dan ISO 27001 Pada Rentang Tahun 2014-2018 di Indonesia

2020

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The use of Information Technology (IT) frameworks from year to year in Indonesia has shown an increase. However, there is not much research on the use of IT frameworks. The research on IT frameworks can be used by a company to analyze trends in the use of frameworks in Indonesia. That way, it can help a company consider choosing a framework to use. The IT frameworks discussed in this study are COBIT, ITIL, and ISO 27001. Data related to research IT frameworks taken in the 2014-2018 period. Data collection through the Google Scholar web search engine using the Publish or Perish software. The data obtained were analyzed using descriptive quantitative methods. The results of this study can use to determine the use of the IT framework in Indonesia. The amount of raw data obtained from the data collection process was 5,708 data with Authors, Title, Years, and Publisher variables. Research data on titles and keywords obtained in the Indonesian domain amounted to 754 and overseas amounted to 194. From the research results, it can conclude that the most widely used framework is the COBIT framework, with a percentage of 69.3% in the Indonesian and 58.7% in the foreign domain.

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“…Execution of the framework is affecting in terms of exactness or computation time. In a number of methodologies, computation is more and it cannot apply inside the real-time environment [20] [21].…”

Section: Related Workmentioning

confidence: 99%

Traffic Signal Data for Emergency Vehicles using C-Means and SVM Classification

Narayanan*,

Saravanan

2020

IJITEE

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Traffic related troubles include not just traffic jamming due to increase in vehicular density, but also complexity for passage of emergency vehicles, violation of rules such as red signal jumps, vehicle breakdowns and accidents causing blockage of roads and loss of lives. Nowadays lot of people losing their lives due to delay of emergency vehicle service. By providing ambulance service timely and accurate can reduce the deaths. By avoiding the unnecessary time delay near traffic jams during an emergency situation. Clustering is a machine learning procedure that includes the gathering of targeted information which is a strategy for unsubstantiated learning and is a typical procedure for factual information investigation utilized in numerous fields. Fuzzy C-means logic is a technique for clustering which enables one bit of information to have a place with two or more clustering. The proposed Fuzzy C-Means (FCM) algorithm technique is often utilized calculation, to inspect the different types of information with the frequent data sets. The Support Vector Machine (SVM) classification method is obviously used classification model which classifies the data entirely however the size is in a common manner. In this paper, a set of datasets is implanted and the experimental clustering report is verified with the frequent parameters such as overlapping, data partitioning, high dimensional data and irrelevant data clustering. On comparing with existing clustering processes, this proposed approach shows the high efficiency than other clustering models with approximate effective results on the association rules.

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Personalized Content Extraction and Text Classification Using Effective Web Scraping Techniques

Cited by 69 publications

References 17 publications

Framing Nuclearity: Online Media Discourses in Lithuania

Framing Nuclearity: Online Media Discourses in Lithuania

Tren Penggunaan Framework COBIT, ITIL, dan ISO 27001 Pada Rentang Tahun 2014-2018 di Indonesia

Traffic Signal Data for Emergency Vehicles using C-Means and SVM Classification

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