This paper presents a detailed survey of word co-occurrence measures used in natural language processing. Word co-occurrence information is vital for accurate computational text treatment, it is important to distinguish words which can combine freely with other words from other words whose preferences to generate phrases are restricted. The latter words together with their typical co-occurring ...

In everyday word learning words are only sometimes heard in the presence of their referent, making the acquisition of novel words a particularly challenging task. The current study investigated whether children (18-month-olds who are novice word learners) can track the statistics of co-occurrence between words and objects to learn novel mappings in a stochastic environment. Infants were briefly...

Background: Co- word analysis is one of the content analysis methods used in scientometric studies and mapping the scientific structure of various fields. The purpose of the present research is to map the structure of distance education using the co-word analysis. Methods: The research method is content analysis using co- word analysis. The research population are 31607 documents indexed in the...

An expanded model for the thermodynamics of co-clusters and their strengthening is presented, and the model is applied to predict co-cluster formation and strengthening in AlMg-Si alloys. The models are tested against data on a wide range of Al-Mg-Si alloys aged at room temperature. The strengthening due to co-clusters is predicted well. The formation of the co-clusters is studied in an Al-0.5a...

To alleviate the data sparseness problem during word alignment, we propose a word alignment method based on word co-occurrence degree. In this paper, we propose a new method to get the statistical information from word cooccurrence. We combine the co-occurrence counts and the fuzzy co-occurrence weights as word co-occurrence degree. Fuzzy co-occurrence weights can be obtained by searching for f...