From words to concepts in Text Mining
نویسنده
چکیده
Text mining processes mostly employ the keyword searches where keywords are extracted from text or using standard thesauri. Key word employment depends on either detecting the significant content reflective words or high frequent words. However, the key word approaches do not ensure semantic retrieval as the confinement of concepts to words is away from reality. Keyword enhancement is applied using term weighting and relevancy ranking in some web processing and search systems. The strength and short comings of these approaches are reviewed in [1].
منابع مشابه
خوشهبندی اسناد مبتنی بر آنتولوژی و رویکرد فازی
Data mining, also known as knowledge discovery in database, is the process to discover unknown knowledge from a large amount of data. Text mining is to apply data mining techniques to extract knowledge from unstructured text. Text clustering is one of important techniques of text mining, which is the unsupervised classification of similar documents into different groups. The most important step...
متن کاملیافتن الگوهای مکرّر در قرآن کریم بهکمک روشهای متنکاوی
Quran’s Text differs from any other texts in terms of its exceptional concepts, ideas and subjects. To recognize the valuable implicit patterns through a vast amount of data has lately captured the attention of so many researchers. Text Mining provides the grounds to extract information from texts and it can help us reach our objective in this regard. In recent years, Text Mining on Quran and e...
متن کاملارائه مدلی برای استخراج اطلاعات از مستندات متنی، مبتنی بر متنکاوی در حوزه یادگیری الکترونیکی
As computer networks become the backbones of science and economy, enormous quantities documents become available. So, for extracting useful information from textual data, text mining techniques have been used. Text Mining has become an important research area that discoveries unknown information, facts or new hypotheses by automatically extracting information from different written documents. T...
متن کاملA Joint Semantic Vector Representation Model for Text Clustering and Classification
Text clustering and classification are two main tasks of text mining. Feature selection plays the key role in the quality of the clustering and classification results. Although word-based features such as term frequency-inverse document frequency (TF-IDF) vectors have been widely used in different applications, their shortcoming in capturing semantic concepts of text motivated researches to use...
متن کاملCompetitive Intelligence Text Mining: Words Speak
Competitive intelligence (CI) has become one of the major subjects for researchers in recent years. The present research is aimed to achieve a part of the CI by investigating the scientific articles on this field through text mining in three interrelated steps. In the first step, a total of 1143 articles released between 1987 and 2016 were selected by searching the phrase "competitive intellige...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- JDIM
دوره 4 شماره
صفحات -
تاریخ انتشار 2006