Sentence examples for document categorization from inspiring English sources

PKIP tool has an advantage over the traditional document categorization methods in that it can correctly categorize the question item which lacks keywords since it adopts the feature selection technique and support vector machine approach to item bank text categorization.

This paper examines several different approaches to exploiting structural information in semi-structured document categorization.

Document categorization is one of the foundational problems in (web) information retrieval.

All of which can be used for setting up more efficient search strategies and facilitated document categorization.

In order to process large numbers of explicit knowledge documents such as patents in an organized manner, automatic document categorization and search are required.

Experiments were performed on text document categorization and ranking tasks.

Document classification and categorization are different processes: classification refers to the assignment one or more predefined categories to a document, while categorization refers to the process of dividing the set of documents into priory unknown groups whose members are in some way similar to each other [35].

Each manually inspected document (classified either as relevant or irrelevant) represents a new addition to the training data used for documentation categorization.

Such analysis is facilitated through use of text mining techniques, ranging from simple statistical pattern learning based on term frequencies, to complex natural language processing techniques in order to produce text categorization, document summarization, information retrieval, and ultimately the data mining [ 6].

Similarly, use topics to representing documents can benefit categorization.

In standard data mining approach to text categorization, documents represent as bag-of-word vectors.