Titlebook: Information Management and Big Data; Second Annual Intern Juan Antonio Lossio-Ventura,Hugo Alatrista-Salas Conference proceedings 2017 Spri

记忆

Dictionary-Based Sentiment Analysis Applied to a Specific Domain,f opinion terms, as well as terms of the domain. In order to select only relevant terms we apply two measures . and .. Experiments conducted on different domains highlight that our automatic approach performs better for specific cases.

符合你规定

An Approach to Evaluate Class Assignment Semantic Redundancy on Linked Datasets,ith more number of instances. In this evaluation we also observed some patterns that can be used to classify class assignments. These observations may be useful for linked data stakeholders to understand how different schemas are used within a dataset, detect errors and improve the mechanisms to generate linked data.

微粒

Big Data Architecture for Predicting Churn Risk in Mobile Phone Companies, customers may go to the competition company, according to their opinions. Data processing is performed by Hadoop, which implements MapReduce and can process large amounts of data in parallel way. After doing the tests and seeing the results, we got a high percentage of accuracy (90.03% of success).

Common-Migraine

Topic-Based Sentiment Analysis,nt points for the polarity words. Our experiments are based on the data from the Semantic Evaluation Exercise 2015 (SemEval-2015), task 10, subtask C. The dependency parser that we used is adapted to this kind of text. Our classifier that combines topic- and sentence-level features obtained very good results.

acolyte

employor

Sense-Level Semantic Clustering of Hashtags,uch as Wordnet and Wikipedia. While immune to the uncontrolled and often sparse usage of hashtags, the current method distinguishes hashtag semantics only at the word-level. Unfortunately, a word can have multiple senses representing the exact semantics of a word, and, therefore, word-level semantic

murmur

Automatic Idiom Recognition with Word Embeddings,tions could improve their performance if idiom recognition were improved. Our approach is based on the idea that idioms and their literal counterparts do not appear in the same contexts. We propose two approaches: (1) Compute inner product of context word vectors with the vector representing a targe

半导体

A Text Mining-Based Framework for Constructing an RDF-Compliant Biodiversity Knowledge Repository,work for automatically transforming text into a structured knowledge repository. A text mining workflow employing information extraction techniques, i.e., named entity recognition and relation extraction, was implemented in the Argo platform and was subsequently applied on biodiversity literature to

Project

高脚酒杯

Dictionary-Based Sentiment Analysis Applied to a Specific Domain,of topics. This constitutes a rich resource for natural language processing tasks, particularly for sentiment analysis. Nevertheless, sentiment analysis is usually difficult because expressed sentiments are usually topic-oriented. In this paper, we propose to automatically construct a sentiment dict