Data mining techniques, including text mining, linguistic feature mining, and classification by text features, can be used to analyze the "caller side" of the transcripts of these calls.
To evaluate the correctness of incremental representation, social text similarity/relatedness, linguistic tasks, network event detection, social user multi-label classification and user clustering for social network analysis are employed as benchmarks in this paper.
To quantify the contribution of word patterns that cannot be explained just by chance, we considered a random version of the text where linguistic order was absent.
Harnad (1989, 1991) claims that a better test than The Turing Test will be one that requires responses to all of our inputs, and not merely to text-formatted linguistic inputs.
But the predominant view was not so extreme: thinking in terms of figures was valued as a means of facilitating grasp of formulae and linguistic text, but only reasoning expressed by means of formulae and text could bear any epistemological weight.
In the end the page has to look good, to convey the weight and sense of its contents clearly, and to provide a text free from linguistic obstacles.
Computer-based text analysis, the linguistic inquiry and word count assessed the dependent variables.
Moreover, Ragan maintains that as for the elaborative text compared to linguistic simplification, modification promoted text coherence.
This process relies on two major phases: The analysis phase refers to the process of structuring text by using linguistic analysis techniques such as recognizing the words, sentences, their grammatical roles and relationships.
As a result of this information explosion, text mining and linguistic methods have been used to perform automatic named entity recognition (NER) including biomedical NER [ 4], the extraction of clinical narratives [ 5] and clinical trials [ 6], analysis of the similarity in gene ontology [ 7], and the prioritization of vital function genes [ 8].
