With the advent of new technology paradigm, SMAC (Social media, Mobile, Analytics and Cloud) the information network generates an infinite ocean of data spreading faster and larger than earlier. A high quality information extracted from this massive volume of data, named as big data, urges the development of an efficient and effective decision support system and powerful strategic tools in the area of government intelligence. This pool of information can be explored for the benefit of an organization/system and to better understand its stakeholder needs by collecting, mining opinions about every point or subject of interest. Digitally intelligent and smart governance has been identified as a dynamic field with new studies being reported at various research avenues. The need to review, analyze and evaluate research studies across literature is thus fostered motivating us to identify existing trends, research gaps and potential directions of future work within this domain. This paper intends to provide a systematic literature review within the promising area of opinion mining and its application to the area of government

https://www.webology.org/2017/v14n2/a156.pdf

Systematic Literature Review on Opinion Mining of Big Data for Government Intelligence.

The invention discloses an open Chinese entity relation extraction method using dependency analysis. According to the method, firstly, sentences are subjected to dependency analysis; then, a Chinese grammar heuristic rule and the dependency analysis result are combined for extracting relation words; next, the named entity position is determined according to the distance; and finally, the triple output is carried out. The experiment is carried out on SogouCA and SogouCS language databases. The result shows that the method provided by the invention is applicable to large-scale language databases, and has good transportability. The method provided by the invention fundamentally overcomes the limitation of intrinsic properties of complicated Chinese grammar, diverse expression modes, rich semantics and the like.

Open Chinese entity relation extraction method using dependency analysis

The embodiment of the invention provides a method for opinion extraction, which comprises that a user's comment aiming at an evaluation object is acquired from a virtual community; word division is carried out to the comment, and a word nature of each word in the comment is acquired; dependency analysis is carried out to the comment according to the word nature of each word to obtain a dependency relation between each word in the comment; and according to the dependency relation between each word in the comment, the user's evaluation opinion aiming at the evaluation object or a preset attribute of the evaluation object is extracted from the comment in the virtual community. By extracting the evaluation opinion according to the dependency relation between each word in the comment, the method provided by the invention significantly increases accuracy of the extracted evaluation opinion and makes the extracted evaluation opinion have strong practicability. In addition, the embodiment of the invention also provides a kind of equipment for the opinion extraction.

Method and equipment for opinion extraction

The invention provides a text message processing method and device, and belongs to the technical field of natural language processing and data mining. The method comprises the following steps: acquiring text message; carrying out participle processing on the text message to obtain a plurality of undetermined terms; acquiring term vectors which respectively correspond to the undetermined terms; calculating the similarity of the term vector corresponding to each undetermined term and the term vector corresponding to each emotion term in a preset emotion dictionary; and judging the emotion attribute of the text message according to the similarity of the term vector corresponding to each undetermined term and the term vector corresponding to each emotion term in the emotion dictionary. Compared with an existing method, the text message processing method and device reduces requirements on the updating speed of the emotion dictionary; the problem of poor emotion analysis effect caused by the reason that the emotion dictionary is not updated in time is avoided; and accuracy of analysis results is improved effectively.

Text message processing method and device

The invention discloses a dependency tree and attention mechanism-based attribute sentiment classification method. The method comprises the steps of selecting a smallest sub-tree part comprising givenattributes based on a dependency tree analysis result of a whole text, and taking clauses of the part as representations of context information of the attributes; then performing modeling on contextsof sentences and contexts of the attributes by utilizing two bidirectional threshold circulation units to obtain two feature representation matrixes fixed in size; obtaining feature representations of the text and specific attributes by utilizing an attention mechanism; and finally performing sentiment polarity classification of the specific attributes by utilizing a multilayer perceptron. The classification method proposed by the invention can extract different attribute feature information for different attributes in the same text, and is high in classification accuracy.

Dependency tree and attention mechanism-based attribute sentiment classification method

The invention discloses a viewpoint extracting method based on a word dependence relationship. The viewpoint extracting method based on the word dependence relationship comprises the steps of: acquiring a word dependence relationship path and establishing a word dependence relationship library; extracting an evaluation object and emotion characteristics by adopting a word dependence relationship chain based matching algorithm; and judging viewpoint polarity through evaluating the word dependence relationship between the evaluation object and the emotion characteristics. The viewpoint extracting method based on the word dependence relationship, disclosed by the invention, has the advantages of extracting viewpoints in different fields and realizing a relatively high viewpoint extracting accuracy rate.

Viewpoint extracting method based on word dependence relationship

The invention discloses an opinion retrieval method based on emotional relevancy. The opinion retrieval method includes steps: calculating text relevancy of a document and a query subject in an algorithm based on a probability retrieval model in a document collection; calculating text relevancy of the document and the query subject in an opinion extraction method based on a word dependence relation path; and combining the text relevancy of the document and the query subject and the emotional relevancy of the document and the query subject in a linear weighting method to determine the final relevance of the text and the query. According to the opinion retrieval method, the tendentious strength of the subject in the test is calculated on the basis of the opinion extraction technology, and the integral relevance of the text and the query is calculated by combining the text relevancy of the document and the query subject and the emotional relevancy of the document and the query subject. In addition, a general knowledge network is adopted to expand the query subject, the relevancy between a query expansion word and the query subject is calculated, and the opinion retrieval effect can be further improved.

Opinion retrieval method based on emotional relevancy

The invention discloses a word semantic tendency prediction method based on a universal knowledge network. The method comprises the following steps of: (1) judging whether an unknown word exists in a sentiment word dictionary, if so, returning the polarity of the unknown word, and otherwise, executing the step (2); (2) selecting a positive reference word set and a negative reference word set; (3) calculating the tightness degree of the unknown word and the positive reference word set; (4) calculating the tightness degree of the unknown word and the negative reference word set; (5) calculating difference between the tightness degree of the unknown word and the positive reference word set and the tightness degree of the unknown word and the negative reference word set; and (6) according to the difference in the step (5), selecting a threshold space and determining the polarity of the unknown word. The word semantic tendency prediction method based on the universal knowledge network has the advantages that the semantic similarity of words is taken into consideration, the association of the words is combined, area threshold judgment is performed, the words are prevented from being endowed with wrong sentiment tendency, and the accuracy of semantic tendency judgment is improved.

Word semantic tendency prediction method based on universal knowledge network

Chinese Multi-document Summarization Based on Opinion Similarity

Automatic opinion mining and summarization from online reviews are very useful for customers and merchants. This paper proposes a method to extract opinions from Chinese product reviews. Firstly, reviews are pre-processed and the sentiment features are extracted based on a sentiment lexicon. Then, it finds out the matching target attribute using the extracted sentiment features base on the using co-occurrence knowledge of topic feature and sentiment feature. After the opinions were found, it generates the summary for products according to the most common opinions.

An Yi

Papers

Viewpoint extracting method based on word dependence relationship

Opinion retrieval method based on emotional relevancy

Word semantic tendency prediction method based on universal knowledge network

Chinese Multi-document Summarization Based on Opinion Similarity

A Method of Extracting Opinion from Chinese Product Review