A semantic framework for textual data enrichment

Gutiérrez, Yoan; Vázquez, Sonia; Montoyo, Andrés

doi:10.1016/j.eswa.2016.03.048

Cited by 17 publications

(15 citation statements)

References 12 publications

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“…In order to solve this problem, a wide variety of systems have been developed to determine the right meaning of words in their different contexts. In fact, WSD has been proven to be necessary to improve the results of other tasks such as Machine Translation [6], [7], [8], Opinion Mining [9], [10] or Recommender Systems [11] among others. WSD is therefore considered to be an essential task for all these applications [12], and it is for this reason that many research groups are working on WSD using a wide range of different approaches.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

Spreading semantic information by Word Sense Disambiguation

Gutiérrez

Vázquez

Montoyo

2017

Knowledge-Based Systems

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This paper presents an unsupervised approach to solve semantic ambiguity based on the integration of the Personalized PageRank algorithm with word-sense frequency information. Natural Language tasks such as Machine Translation or Recommender Systems are likely to be enriched by our approach, which includes semantic information that obtains the appropriate word-sense via support from two sources: a multidimensional network that includes a set of different resources (i.e. WordNet, WordNet Domains, WordNet Affect, SUMO and Semantic Classes); and the information provided by word-sense frequencies and word-sense collocation from the SemCor Corpus. Our series of results were analyzed and compared against the results of several renowned studies using SensEval-2, SensEval-3 and SemEval-2013 datasets. After conducting several experiments, our procedure produced the best results in the unsupervised procedure category taking SensEval campaigns rankings as reference.

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Section: Accepted Manuscriptmentioning

confidence: 99%

Spreading semantic information by Word Sense Disambiguation

Gutiérrez

Vázquez

Montoyo

2017

Knowledge-Based Systems

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“…This task detects the meaning of sentence using probabilistic semantic models. Paper [14] is focused on ISR-WN which is able to detect domains or categories from dierent resources obtaining and using relevant semantic trees from a text.…”

Section: Time Expression Recognition: Time Expression Recognition Tasmentioning

confidence: 99%

A Document Profile for Improving Information Retrieval Systems

Guillén¹,

Gutiérrez²,

Muñoz³

2017

RCS

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In recent year the great popularity that enjoys mobile technologies has led most users to become consumers and producers of information on the network. Many studies speak about this phenomenon as an activity that is capable of doubling or tripling existing content on an annual basis. The huge amount of information makes the current user oriented systems, like retrieval systems, recommender systems and others, become less ecient, especially when users require specic information and answers according to their needs and preferences. These facts make necessary to equip these systems with proper Natural Language technologies able to provide the information that users demand adapted to each context and content type. In this article, it is presented a study of some Natural Language Processing technologies that can be useful to facilitate the proper identication of documents according to the user needs. For this purpose, it is designed a document prole that will be able to represent semantic meta-data extracted from documents. The research is basically focused on the study of dierent language technologies in order to support the creation this novel document prole proposal from semantic perspectives.

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“…A semantic framework for textual data is used as sustained tool for recommender systems. This approach combines and uses different NLP tasks to measure the similarity, semantic analysis and rate of the sentiments are discussed [12]. A methodology to identify emotions in online customer reviews in order to determine the various emotion dimensions in various different products are analysed.…”

Section: Dictionary Based Approachmentioning

confidence: 99%

Perspectives of the performance metrics in lexicon and hybrid based approaches: a review

Rani¹,

Sumathy²

2017

IJET

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Online social media and social networking services experience a drastic development in the present scenario. Contents generated by hundreds of millions of users are used for communication in general. Users mark their opinion and review in various applications such as Twitter, Facebook, YouTube, Weibo, Flicker, LinkedIn, Online-e commerce sites, Microblogging sites, etc. User generated text is spread rapidly on the web, and it has become tedious to analyze the opinionated text in order to arrive at a decision. Sentiment analysis, a subcategory of text mining is the major active research domain in current era due to greater quantity of opinionated text present in the Internet. Semantic detection is the sub-class in the sentiment analysis which is used for measuring the sentiment orientation in any text. Opinionated text is used for analyzing and making the decision simple. This interdisciplinary field draws various techniques from data mining, machine learning, natural language processing, lexicon based and hybrid based approaches. This paper provides a broad perspective with the highlight of the current state-of art techniques emphasizing the various research challenges and gaps present. The performance metrics in terms of detection rate, precision, recall, f-measure/score, average mean, auto-Pearson correlation, cosine similarity and ratio of time on various algorithms is discussed in detail. An analysis of the text mining approaches in different domains is presented.

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A semantic framework for textual data enrichment

Cited by 17 publications

References 12 publications

Spreading semantic information by Word Sense Disambiguation

Spreading semantic information by Word Sense Disambiguation

A Document Profile for Improving Information Retrieval Systems

Perspectives of the performance metrics in lexicon and hybrid based approaches: a review

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