Text Trend Analysis via Significant Term A Based on Indonesia News

Text Trend Analysis via Significant Term A Based on Indonesia News

Arie Budiansyah(Arie Budiansyah)

指導教授 ： 王經篤

亞洲大學/資訊學院/資訊工程學系碩士班/碩士(2010年)

摘要

The thesis provides the frequency distribution of significant terms
over past time periods for text trend analysis via an Indonesia newspaper.
The approach consists of two steps:(1) Data Preprocessing
(2) Term History Generation. The former adopts agent techniques
to download the news articles automatically and extracts the contents
of these articles. The later uses an existing external memory
approach to extract significant terms while computing the term history
simultaneously. One significant term, in this study, is a series
of words that were significant enough to present one event, action
or concept. The term history of one term is the frequency distribution
of that term over consecutive time periods as a time series
data. The experimental resources includes one year of Indonesia
newspaper, ”Serambi”, containing 28, 071 articles. Experimental result
shows that it is attractive and meanful for foreigners who desire
to know the trend and situation happened in Aceh province of Indonesia,
where the majority of Serambi newspaper concerned with.
Keywords: significant term, trend analysis, text mining

關鍵字

trend analysis ； text mining ； significant term ； information retrieval

並列摘要

The thesis provides the frequency distribution of significant terms
over past time periods for text trend analysis via an Indonesia newspaper.
The approach consists of two steps:(1) Data Preprocessing
(2) Term History Generation. The former adopts agent techniques
to download the news articles automatically and extracts the contents
of these articles. The later uses an existing external memory
approach to extract significant terms while computing the term history
simultaneously. One significant term, in this study, is a series
of words that were significant enough to present one event, action
or concept. The term history of one term is the frequency distribution
of that term over consecutive time periods as a time series
data. The experimental resources includes one year of Indonesia
newspaper, ”Serambi”, containing 28, 071 articles. Experimental result
shows that it is attractive and meanful for foreigners who desire
to know the trend and situation happened in Aceh province of Indonesia,
where the majority of Serambi newspaper concerned with.
Keywords: significant term, trend analysis, text mining

並列關鍵字

trend analysis ； text mining ； significant term ； information retrieval

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