Title :
E-mail Clustering Based on Profile and Multi-attribute Values
Author :
Lee, Samuel Sangkon ; Shishibori, Masami ; Ando, Kazuaki
Abstract :
Although modern day people gather many data from the network, the users want only the information needed. Using this technology, the users can extract on the data that satisfy the query. As the previous studies use the single data in the document, frequency of the data for example, it cannot be considered as the effective data clustering method. What is needed is the effective clustering technology that can process the electronic network documents such as the e-mail or XML that contain the tags of various formats. This paper describes the study of extracting the information from the user query based on the multi-attributes. It proposes a method of extracting the data such as the sender, text type, time limit syntax in the text, and title from the e-mail and using such data for filtering. It also describes the experiment to verify that the multi-attribute based clustering method is more accurate than the existing clustering methods using only the word frequency.
Keywords :
Chapters; Clustering methods; Data mining; Electronic mail; Frequency; Information filtering; Information filters; Information technology; Search engines; XML; E-mail ClusteringProfile InformationMulti-attribute ValueNatural Language ProcessingInformation Retrieval;
Conference_Titel :
Advanced Language Processing and Web Information Technology, 2007. ALPIT 2007. Sixth International Conference on
Conference_Location :
Luoyang, Henan, China
Print_ISBN :
978-0-7695-2930-1
DOI :
10.1109/ALPIT.2007.14