Self-adaptive ontology-based focused crawling: A literature survey

Khan, Mohd. Aamir; Sharma, Dilip Kumar

doi:10.1109/icrito.2016.7785024

Cited by 5 publications

(3 citation statements)

References 22 publications

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“…The main role of the web crawler is to simplify and to automate the entire crawling process and makes the data crawling easy and accessible to everyone. According to the [5], crawlers are classified into two main categories: classical (traditional) crawlers and focused crawlers. The classical (traditional) web crawlers navigate the webpages and gather both relevant and irrelevant information which is a huge waste of crawling time and the storage of the downloaded information [6] Focused crawlers do not crawl the whole web as opposed to the traditional crawlers, as they only crawl to the deepest the specific part of the web that is related to the given topic.…”

Section: Data Extractionmentioning

confidence: 99%

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Financial Banking Dataset for Supervised Machine Learning Classification

Raicu¹

2019

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Social media has opened new avenues and opportunities for financial banking institutions to improve the quality of their products and services and to understand and to adapt to their customers' needs. By directly analyzing the feedback of its customers, financial banking institutions can provide personalized products and services tailored to their customer needs. This paper presents a research framework for creation of a financial banking dataset in order to be used for Sentiment Classification using various Machine Learning methods and techniques. The dataset contains 2234 financial banking comments from Romanian financial banking social media collected via web scraping technique.

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Section: Data Extractionmentioning

confidence: 99%

“…Financial banking institution (4). Financial banking product (5). Characteristics that have been evaluated by the users (6).…”

Section: Data Storagementioning

confidence: 99%

Financial Banking Dataset for Supervised Machine Learning Classification

Raicu¹

2019

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“…Because of this, traditional crawlers extract a large amount of data and often a big part of it proves to be irrelevant to users. [13] On the other hand, topic crawlers are agents that collect web pages that satisfy certain specific properties. They offer the possibility of downloading relevant web documents for a predefined domain, providing the most up-todate resources (web pages) relevant to the needs of users, with minimum consumption of resources such as storage, time and network bandwidth.…”

Section: Web Data Extractionmentioning

confidence: 99%