Concepts inApplying skip-gram word estimation and SVM-based classification for opinion mining Vietnamese food places text reviews

Sentiment analysis

Sentiment analysis or opinion mining refers to the application of natural language processing, computational linguistics, and text analytics to identify and extract subjective information in source materials. Generally speaking, sentiment analysis aims to determine the attitude of a speaker or a writer with respect to some topic or the overall contextual polarity of a document.  more from Wikipedia

Support vector machine

A support vector machine (SVM) is a concept in statistics and computer science for a set of related supervised learning methods that analyze data and recognize patterns, used for classification and regression analysis. The standard SVM takes a set of input data and predicts, for each given input, which of two possible classes forms the input, making the SVM a non-probabilistic binary linear classifier.  more from Wikipedia

Statistical classification

In machine learning and statistics, classification is the problem of identifying which of a set of categories (sub-populations) a new observation belongs, on the basis of a training set of data containing observations (or instances) whose category membership is known. The individual observations are analyzed into a set of quantifiable properties, known as various explanatory variables, features, etc. These properties may variously be categorical (e.g.  more from Wikipedia

Food

Food is any substance consumed to provide nutritional support for the body. It is usually of plant or animal origin, and contains essential nutrients, such as carbohydrates, fats, proteins, vitamins, or minerals. The substance is ingested by an organism and assimilated by the organism's cells in an effort to produce energy, maintain life, or stimulate growth. Historically, people secured food through two methods: hunting and gathering, and agriculture.  more from Wikipedia

Unstructured data

Unstructured Data (or unstructured information) refers to information that either does not have a pre-defined data model and/or does not fit well into relational tables. Unstructured information is typically text-heavy, but may contain data such as dates, numbers, and facts as well. This results in irregularities and ambiguities that make it difficult to understand using traditional computer programs as compared to data stored in fielded form in databases or annotated in documents.  more from Wikipedia

Machine learning

Machine learning, a branch of artificial intelligence, is a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data, such as from sensor data or databases. A learner can take advantage of examples (data) to capture characteristics of interest of their unknown underlying probability distribution. Data can be seen as examples that illustrate relations between observed variables.  more from Wikipedia

Knowledge representation and reasoning

Knowledge representation (KR) is an area of artificial intelligence research aimed at representing knowledge in symbols to facilitate inferencing from those knowledge elements, creating new elements of knowledge. The KR can be made to be independent of the underlying knowledge model or knowledge base system (KBS) such as a semantic network.  more from Wikipedia

Word

In language, a word is the smallest element that may be uttered in isolation with semantic or pragmatic content (with literal or practical meaning). This contrasts with a morpheme, which is the smallest unit of meaning but will not necessarily stand on its own. A word may consist of a single morpheme, or several (rocks, redness, quickly, running, unexpected), whereas a morpheme may not be able to stand on its own as a word (in the words just mentioned, these are -s, -ness, -ly, -ing, un-, -ed).  more from Wikipedia