Cosh, K.J.; Burns, R.; Daniel, T.: Content clouds : classifying content in Web 2.0 (2008)
0.00
0.0017848461 = product of:
0.010709076 = sum of:
0.010709076 = weight(_text_:in in 2013) [ClassicSimilarity], result of:
0.010709076 = score(doc=2013,freq=8.0), product of:
0.059380736 = queryWeight, product of:
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.043654136 = queryNorm
0.18034597 = fieldWeight in 2013, product of:
2.828427 = tf(freq=8.0), with freq of:
8.0 = termFreq=8.0
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.046875 = fieldNorm(doc=2013)
0.16666667 = coord(1/6)
- Abstract
- Purpose - With increasing amounts of user generated content being produced electronically in the form of wikis, blogs, forums etc. the purpose of this paper is to investigate a new approach to classifying ad hoc content. Design/methodology/approach - The approach applies natural language processing (NLP) tools to automatically extract the content of some text, visualizing the results in a content cloud. Findings - Content clouds share the visual simplicity of a tag cloud, but display the details of an article at a different level of abstraction, providing a complimentary classification. Research limitations/implications - Provides the general approach to creating a content cloud. In the future, the process can be refined and enhanced by further evaluation of results. Further work is also required to better identify closely related articles. Practical implications - Being able to automatically classify the content generated by web users will enable others to find more appropriate content. Originality/value - The approach is original. Other researchers have produced a cloud, simply by using skiplists to filter unwanted words, this paper's approach improves this by applying appropriate NLP techniques.
