Automatic Amharic News Text Summarizer (Extraction)
No Thumbnail Available
Date
2001-06
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Addis Ababa University
Abstract
It is visible that the amount of textual information output is highly
increasing from day to day. Compared to the text output the human capacity of
reading is almost negligible. This big difference creates a problem in
communicating information to the best possible extent. Managing the output also
becomes very difficult. Tasks of sorting, searching through and categorizing are
turning out to be cumbersome. The limited carrying capacities of the
communication channels also require huge reduction in size.
The focus of this research is on development of a mechanism for
shortening Amharic news texts and for producing concise summaries of them. The
system !lies to pin point the most important sentences of the original text and
extract them as a summary of the news. Thus the extract is a lot shorter and
painless to handle.
The proposed summarizer uti I izes several statistical techniques, location
heuristics and diagnostic units to determine the parts of the text to be extracted.
Selected information retrieval and text mining techniques are adopted to build a
model for the proposed system.
The application of the system alter adjusting the weight of its diagnostic
units by using four Amharic news items in 124 different ways reveals a promising
result in automating the task of generating news summaries. Human generated
summaries are used for adjusting weight and evaluating the system. Finally 58%
Recall and 70.4% Precision values are attained. Based on this result, further work
is recommended for future improvements of this system and studies in the area of
automatic Amharic text summarize
Description
Keywords
Information Science