TOWARDS REQUIREMENTS REUSE: IDENTIFYING SIMILAR REQUIREMENTS WITH LATENT SEMANTIC ANALYSIS AND CLUSTERING ALGORITHMS
Published In: 2ND INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATION AND INFORMATION TECHNOLOGY
Author(s): NOOR HASRINA BAKAR , ZARINAH M. KASIRUN
Abstract: Software requirements that exist in natural language can easily be understood by various stakeholders. However, when it comes to extracting common requirements from the natural language requirement documents for reuse, manual extraction process can be arduous, expensive, and very error-prone on the results. In this paper, we describe a process of identifying similar requirement documents for reuse in Software Product Lines. Online product reviews were extracted and used as the input mainly due to the scarcity of publicly available requirement documents. Latent Semantic Analysis technique from Information Retrieval was used to identify similar requirement documents and filter out the unrelated ones after the text has been pre-processed. Similar documents were then clustered together by using K-means and Hierarchical Agglomerative Clustering algorithm. As a result, the output from the clustering process will be used to recommend group of related requirement documents to be used in requir
- Publication Date: 17-Nov-2014
- DOI: 10.15224/978-1-63248-051-4-20
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A REVERSIBLE AND IMPERCEPTIBLE ACOUSTIC WATERMARKING USING PARTIALLY-APPLIED HUFFMAN LOSSLESS COMPRESSION
Published In: 2ND INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATION AND INFORMATION TECHNOLOGY
Author(s): XUPING HUANG
Abstract: In this paper, a reversible and robust acoustic watermarking based on lossless compression is proposed. Stereo speech data is represented by 16 bit for each sampling point and then divided into frames. Then Huffman lossless compression algorithm is applied to insignificant 4 bits in each sampling point partiality to reserve hiding capacity. An average of 0.7035 and the best 0.686 compression ratio depending on different frame lengths are achieved, which promises about 1.188 bits for payload hiding in each sampling point. Since Huffman algorithm is applied partially to each sampling point, stego data is comprehensive after embedding and complexity towards attack is promising. Result of Perceptual Evaluation of Speech Quality based on ITU-T recommendation P.862 and signal-noise ratio (SNR) show the proposed method achieved imperceptibility.
- Publication Date: 17-Nov-2014
- DOI: 10.15224/978-1-63248-051-4-21
- Views: 0
- Downloads: 0