natural language processing software

A very important research direction in natural language processing (NLP) is semantic affective analysis (sentiment). For example, there are a lot of comments about movies on the IMDB, so we can evaluate the reputation of a movie by sentiment analysis, if it's just released, and even predict whether it can make a box-office hit. Similar to this, the domestic water

Zhou Xi Order[Email protected]2001-11-8In most cases, I am used to studying objects that are far from our subjective world. The typical example is "Celestial Bodies". In the process of research, the method used is "building a model". The progress of the research is mainly manifested as "the gradual refinement of the model".For example, a system model of two celestial bodies was initially studied, and the results were basically consistent with the actual data, but with slight differences. Thus, w

Preface: In the natural language processing of the road, unconsciously gradually drift away, looking for information to see a lot of tools, also read a lot of documents, still have a bad life. Accumulate too little, look for more information, although the actual application is very few, recorded the exposure of some NLP tools. Update in ...First, NER (named entit

Python-based Natural Language Processing Toolkit: NLPT (Natural Language Processing toolkit), sudo pip-u install when installed NLTKNLPT's websiteNatural Language

Natural language Processing: Background and overviewNatural Language Processing:background and OverviewAuthor: Regina Barzilay (Mit,eecs Department,september 8, 2004)Translator: I love natural language

parameters, complex page interaction and other issues. Often using tools such as the above can easily solve these problems, the biggest drawback is due to the real browser based on the operation, it is less efficient, so often need and httpclient combination, to achieve efficient and practical purposes. Based on Phantomjs do Baidu meta-search capture also proves this point, the next step can be combined with it to complete the simulation of micro-Bo crawler to get the cookie part, after the use

, this process is called text mining when the object of the data mining is composed entirely of the data type of the text.text mining not only handles a large amount of structured and unstructured document data, but also deals with complex semantic relationships, so most of the existing data mining techniques cannot be applied directly to them. For unstructured problems, one way is to develop a new data mining algorithm directly to the unstructured data mining, the data is very complex, resultin

Any language can be considered asEncoding MethodThe language's syntax rules are the encoding and decoding algorithms. We send the meaning we want to express through a sentence (an encoding). The person who hears this sentence (receives the encoding information) understands this sentence (Decoding ), to understand what the other party wants to express. This is an interesting and vivid process. Natural

The basis of text sentiment analysis is natural language processing, affective dictionary, machine learning method and so on. Here are some of the resources I've summed up.Dictionary resources:Sentiwordnet"Knowledge Network" Chinese versionChinese Affective polarity dictionary NTUSDEmotion Vocabulary Ontology DownloadNatural