Hussam M. Dahwa Abdulla

Survey of Plagiarism Detection Methods

Plagiarism has become one area of interest for researchers due to its importance, and its fast growing rates. In this paper we are going to survey and list the advantage sand disadvantages of the latest and the important effective methods used or developed in automatic plagiarism detection, according to their result. Mainly methods used in natural language text detection, index structure, and external plagiarism detection and clustering -- based detection.

Using Kohonen Maps and Singular Value Decomposition for Plagiarism Detection

Plagiarism has become one area of interest for re-searchers due to its importance, and its fast growing rates. Effective clustering methods and faster search tools for matching and discovering the similarities between documents were the main two areas for the researchers. Many tools and techniques have been developed for plagiarism detection. In this paper we use singular value decomposition for its effective clustering of the documents in-order to reduce search time by creating a new matrix with fewer dimensions used for clustering the original (source) documents, and we use Neural Networks for local matching and comparison between a suspicious document and a source document, Kohonen maps (Self-organizing maps (SOM)) used to visualized and comparison of the result, in which represent the result as picture that easier to be analyzed.

Using a Matrix Decomposition for Clustering Data

There are many search engines in the web and when asked, they return a long list of search results, ranked by their relevancies to the given query. Web users have to go through the list and examine the titles and (short) snippets sequentially to identify their required results. In this paper we present how usage of Matrix Decomposition (Singular Value Decomposition (SVD) and Nonnegative Matrix Factorization (NMF)) can be good solution for the search results clustering.

A New Search Result Clustering Using Haar Wavelet Transform

In traditional search engines, it is not so easy for users to find relevant Web pages list (snippet) of a given query. Therefore, there is a need to retrieve and find the relevant information in a better way by clustering the search results. This paper presents a new approach for clustering search results using Haar wavelet transform. We explain how uses of Haar wavelet transform offer a reasonably good solution for the above.

Search Results Clustering Using Nonnegative Matrix Factorization (NMF)

There are many search engines in the web and when asked, they return a long list of search results, ranked by their relevancies to the given query. Web users have to go through the list and examine the titles and (short) snippets sequentially to identify their required results. In this paper we present how usage of Nonnegative Matrix Factorization (NMF) can be good solution for the search results clustering.

Simple Rules for Syllabification of Arabic Texts

The Arabic language is the sixth most used language in the world today. It is also used by United Nation. Moreover, the Arabic alphabet is the second most widely used alphabet around the world. Therefore, the computer processing of Arabic language or Arabic alphabet is more and more important task. In the past, several books about analyzing of the Arabic language were published. But the language analysis is only one step in the language processing. Several approaches to the text compression were developed in the field of text compression. The first and most intuitive is character based compression which is suitable for small files. Another approach called word-based compression become very suitable for very long files. The third approach is called syllable-based, it use syllable as basic element. Algorithms for the syllabification of the English, German or other European language are well known, but syllabification algorithms for Arabic and their usage in text compression has not been deeply investigated. This paper describes a new and very simple algorithm for syllabification of Arabic and its usage in text compression.

Search Result Clustering using a Singular Value Decomposition (SVD)

There are many search engines in the web, but they return along list of search results, ranked by their relevancies to the given query. Web users have to go through the list and examine the titles and (short) snippets sequentially to identify their required results. In this paper we present usage of Singular Value Decomposition (SVD) as a very good solution for search results clustering.

Clustering data using a Nonnegative Matrix Factorization (NMF)

There are many search engines in the web and when asked, they return a long list of search results, ranked by their relevancies to the given query. Web users have to go through the list and examine the titles and (short) snippets sequentially to identify their required results. In this paper we present how usage of Nonnegative Matrix Factorization (NMF) can be good solution for the search results clustering.

Application of Binocular Vision and Diamond Search Technology in Computer Vision Navigation

Mobile tracking robot will play an important role in our future life. Target recognition, distance estimation and motion estimation are three primary functions of this kind of robot, respectively. Consequently, the irrelevant three technologies, pattern recognition, binocular vision and fast block-matching algorithm, make up of a novel approach of computer vision navigation for mobile tracking robot. This novel approach is analyzed in this paper with emphasis on distance estimation and motion estimation. Extended discussion of several interesting observations are also presented. Experimental results show the validity of the approach. Integrating the key components together, a simplified verification frame based on LEGO Mindstorms NXT is designed to check the three technologies combination.

Web retrieval improvement: Using pattern detection

In our paper, we work with our own Pattrio method of analysis of web pages, which is based on using web design patterns. The method is based on a silent agreement between web designers and users. The key aspects of this agreement are web patterns which are used by web designers in their web page implementations and are language independent. We use our method for analysing web pages in selling product domain. In our earlier experiments we worked with pages in Czech and English. In this paper, we present an experiment with pages in Arabic language. Our experiments show efficiency of the method and possible usefulness of our approach for multi-language retrieval.