A New Text Mining Approach Based on HMM-SVM for Web News Classification

Krishnalal, G; Rengarajan, S Babu; Srinivasagan, K. G.

doi:10.5120/395-589

Cited by 24 publications

(15 citation statements)

References 36 publications

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“…We have conjointly projected a collection of recent options to represent a 1 second sub clip, as well as band regularity , LSP divergence form and spectrum flux. Krishnlal G, S adult male Rengarajan, K G Srinivasagan [6] The intelligent news classifier is developed and experimented with on-line news from internet for the class sports, finance and politics. The noval approach combining 2 powerful algorithms, Hidden mathematician Model and Support vector machine, within the on-line news classification domain provides extraordinarily smart result compared to existing methodologies.…”

Section: Related Workmentioning

confidence: 99%

A Review on Automatic News Classification using the Probabilistic Classification Algorithms

2016

IJSR

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Reviews are unbiased information obtained from the sources outside an organization, which makes them more reliable in the eyes of customers. Online shoppers are very much concerned about product reviews before making any decision regarding buying the product. Product reviews plays an important role in determining what kind of product is. Such reviews provide useful information about customer concern and their experience with the product. Consequently, these reviews will be helpful for a business making products for the purpose of product recommendation, better customer understanding and attracting more loyal customers. As ecommerce has become so popular, numbers of reviews are increasing day by day. It is difficult for a customer to read all the reviews manually. In this paper, an approach is developed which is used to obtain the summary from thousands or hundreds of online reviews. This approach uses extraction summarization for summarizing the reviews thereby selecting the original sentences and putting it together into a new shorter text explaining the overall opinion about the product. Although previous studies of deriving useful information from customer reviews focus on categorical or numerical data and textual data has been ignored. But textual data are of equal importance so it should not be ignored. So, this approach includes every aspect of the review in the summary so that a customer would be able to make a right decision regarding product.

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Section: Related Workmentioning

confidence: 99%

A Review on Automatic News Classification using the Probabilistic Classification Algorithms

2016

IJSR

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“…A POS-tagger should segment a word, determine its possible readings, and assign the right reading given the context. In this case, we consider a stochastic tagger Hidden Markov Model (pos-en-general-brown.HMM) [7][8]as corpus for POSTagging. …”

Section: Postaggingmentioning

confidence: 99%

Statistical estimation of emotions in speech notes by featured term analogy

Sita

Suhasini

Mohd.

2011

2011 International Conference on Image Information Processing

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Human Being is the only creature in the World who can express his emotions in various forms. Capturing the extent of emotions in a particular speech notes through quantification of verbal expressions is undoubtedly a challenging area to study. Either positive or negative, whatever be the emotions are in the notes, if we succeed in assessing the degree of positiveness or negativeness, the impact of the notes while addressing to the intended people can be pre-estimated easily. This paper presents a brief idea of how we can statistically estimate the emotional characteristics of a speech notes by analyzing the content in the speech notes through Information Extraction. Since it is mandatory for any sentence to have atleast a verb, we primarily concentrate on the verbs as featured terms in each sentence and there by statistically estimate the rigorousness of the verb on the entire speech note. The strength of the verb in its severity can be measured by comparing it with strong, medium, light corpus of emotions developed specially. This enables to judge the effectiveness of a speech notes in various emotions.

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“…Most items in a cluster are very similar, and while some articles may bring more details or talk about a speci c aspect of the topic at hand, it is assumed that users will most o en read only one of the news pieces. Groups of clusters are sometimes arranged in topical categories to lower the information overload [10]. However, when considering more than a day worth of news, clustering leads to the creation of a large number of small sets of articles that are hard to comprehend.…”

Section: Standard Approachesmentioning

confidence: 99%

Linking Multimedia Content for Efficient News Browsing

Bois

Gravier

Jamet

et al. 2017

Proceedings of the 2017 ACM on International Conference on Multimedia Retrieval

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As the amount of news information available online grows, media professionals are in need of advanced tools to explore the information surrounding speci c events before writing their own piece of news, e.g., adding context and insight. While many tools exist to extract information from large datasets, they do not o er an easy way to gain insight from a news collection by browsing, going from article to article and viewing unaltered original content. Such browsing tools require the creation of rich underlying structures such as graph representations. ese representations can be further enhanced by typing links that connect nodes, in order to inform the user on the nature of their relation. In this article, we introduce an e cient way to generate links between news items in order to obtain an easily navigable graph, and enrich this graph by automatically typing created links. User evaluations are conducted on real world data in order to assess for the interest of both the graph representation and link typing in a press reviewing task, showing a signi cant improvement compared to classical search engines.

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A New Text Mining Approach Based on HMM-SVM for Web News Classification

Cited by 24 publications

References 36 publications

A Review on Automatic News Classification using the Probabilistic Classification Algorithms

A Review on Automatic News Classification using the Probabilistic Classification Algorithms

Statistical estimation of emotions in speech notes by featured term analogy

Linking Multimedia Content for Efficient News Browsing

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