Queuing is one of the most usable tools that help in analyzing the performance of complex telecom... more Queuing is one of the most usable tools that help in analyzing the performance of complex telecommunication and system networks. Thus, this term paper presents the performance measurements of computer networks with queuing technique. The paper covers the detail introduction of queuing theory and its various applications widely used for complex network/system environment.
The measurement of the relatedness of word semantics based on complementary Wikipedia and WordNet... more The measurement of the relatedness of word semantics based on complementary Wikipedia and WordNet-based methods takes two forms, combined and integrative, which are aimed at increasing the semantic space between related words. However, each form has its own set of issues regarding its components and the strategy that is used to combine and integrate corpus-based and knowledge-based methods. In the integrative strategy, a large corpus, such as Wikipedia, is used to extract a set of related words for a particular concept as a basis for searching the WordNet space. The drawback to this strategy is in its use of a fixed scaling parameter, which only fits an implemented dataset that is near to a human score. Other corpusbased methods use a cutoff threshold that is determined experimentally to reduce the semantic space and to increase the search for a more accurate semantic space. Such methods merely take into account the frequency of bigrams, while ignoring the frequency of individual terms. Knowledge-based methods using a gloss overlap have a similar limitation to the corpus-based methods, where they lead to the loss of many valuable relatedness features that determine a more accurate measurement. Thus, in this paper, a new Information Content Glossary Relatedness (ICGR) approach was proposed in two steps, namely, an Extended-PMI based on a cutoff density threshold was proposed to extract a Robust Relatedness Vector set (RVS) of a large Wikipedia dataset. Then, a Semantic Structural Information (SSI) method was presented to use the RVS as a fulcrum to define the most relatedness gloss in the WordNet of each gloss and to select the top 5 glosses related to each RVS. The results showed that the proposed approach outperformed the state-of-the-art set, where the Extended-PMI achieved a Spearman's correlation of 0.89 to the human score and the ICGR approach achieved a Spearman's correlation of 0.8 to the human score.
Automatic Essay Grading (AEG) system is defined as the computer technology that evaluates and gra... more Automatic Essay Grading (AEG) system is defined as the computer technology that evaluates and grades written prose. The short essay answer, where the essay is written in short sentences where it has two types the open ended short answer and the close ended short answer where it is our research domain based on the computer subject. The Marking of short essay answers automatically is one of the most complicated domains because it is relying heavily on the semantic similarity in meaning refers to the degree to which two sentences are similar in the meaning where both used similar words in the meaning, in this case Humans are able to easily judge if a concepts are related to each other, there for is a problem when Student use a synonym words during the answer in case they forget the target answer and they use their alternative words in the answer which will be different from the Model answer that prepared by the structure. The Standard text similarity measures perform poorly on such tasks. Short answer only provides a limited content, because the length of the text is typically short, ranging from a single word to a dozen words. This research has two propose; the first propose is Alternative Sentence Generator Method in order to generate the alternative model answer by connecting the method with the synonym dictionary. The second proposed three algorithms combined together in matching phase, Commons Words (COW), Longest Common Subsequence (LCS) and Semantic Distance (SD), these algorithms have been successfully used in many Natural Language Processing systems and have yielded efficient results. The system was manually tested on 40 questions answered by three students and evaluated by teacher in class. The proposed system has yielded %82 correlation-style with human grading, which has made the system significantly better than the other state of the art systems.
The measurement of the relatedness of word semantics based on complementary Wikipedia and WordNet... more The measurement of the relatedness of word semantics based on complementary Wikipedia and WordNet-based methods takes two forms, combined and integrative, which are aimed at increasing the semantic space between related words. However, each form has its own set of issues regarding its components and the strategy that is used to combine and integrate corpus-based and knowledge-based methods. In the integrative strategy, a large corpus, such as Wikipedia, is used to extract a set of related words for a particular concept as a basis for searching the WordNet space. The drawback to this strategy is in its use of a fixed scaling parameter, which only fits an implemented dataset that is near to a human score. Other corpusbased methods use a cut-off threshold that is determined experimentally to reduce the semantic space and to increase the search for a more accurate semantic space. Such methods merely take into account the frequency of bigrams, while ignoring the frequency of individual terms. Knowledge-based methods using a gloss overlap have a similar limitation to the corpus-based methods, where they lead to the loss of many valuable relatedness features that determine a more accurate measurement. Thus, in this paper, a new Information Content Glossary Relatedness (ICGR) approach was proposed in two steps, namely, an Extended-PMI based on a cut-off density threshold was proposed to extract a Robust Relatedness Vector set (RVS) of a large Wikipedia dataset. Then, a Semantic Structural Information (SSI) method was presented to use the RVS as a fulcrum to define the most relatedness gloss in the WordNet of each gloss and to select the top 5 glosses related to each RVS. The results showed that the proposed approach outperformed the state-of-the-art set, where the Extended-PMI achieved a Spearman's correlation of 0.89 to the human score and the ICGR approach achieved a Spearman's correlation of 0.8 to the human score.
Queuing is one of the most usable tools that help in analyzing the performance of complex telecom... more Queuing is one of the most usable tools that help in analyzing the performance of complex telecommunication and system networks. Thus, this term paper presents the performance measurements of computer networks with queuing technique. The paper covers the detail introduction of queuing theory and its various applications widely used for complex network/system environment.
The measurement of the relatedness of word semantics based on complementary Wikipedia and WordNet... more The measurement of the relatedness of word semantics based on complementary Wikipedia and WordNet-based methods takes two forms, combined and integrative, which are aimed at increasing the semantic space between related words. However, each form has its own set of issues regarding its components and the strategy that is used to combine and integrate corpus-based and knowledge-based methods. In the integrative strategy, a large corpus, such as Wikipedia, is used to extract a set of related words for a particular concept as a basis for searching the WordNet space. The drawback to this strategy is in its use of a fixed scaling parameter, which only fits an implemented dataset that is near to a human score. Other corpusbased methods use a cutoff threshold that is determined experimentally to reduce the semantic space and to increase the search for a more accurate semantic space. Such methods merely take into account the frequency of bigrams, while ignoring the frequency of individual terms. Knowledge-based methods using a gloss overlap have a similar limitation to the corpus-based methods, where they lead to the loss of many valuable relatedness features that determine a more accurate measurement. Thus, in this paper, a new Information Content Glossary Relatedness (ICGR) approach was proposed in two steps, namely, an Extended-PMI based on a cutoff density threshold was proposed to extract a Robust Relatedness Vector set (RVS) of a large Wikipedia dataset. Then, a Semantic Structural Information (SSI) method was presented to use the RVS as a fulcrum to define the most relatedness gloss in the WordNet of each gloss and to select the top 5 glosses related to each RVS. The results showed that the proposed approach outperformed the state-of-the-art set, where the Extended-PMI achieved a Spearman's correlation of 0.89 to the human score and the ICGR approach achieved a Spearman's correlation of 0.8 to the human score.
Automatic Essay Grading (AEG) system is defined as the computer technology that evaluates and gra... more Automatic Essay Grading (AEG) system is defined as the computer technology that evaluates and grades written prose. The short essay answer, where the essay is written in short sentences where it has two types the open ended short answer and the close ended short answer where it is our research domain based on the computer subject. The Marking of short essay answers automatically is one of the most complicated domains because it is relying heavily on the semantic similarity in meaning refers to the degree to which two sentences are similar in the meaning where both used similar words in the meaning, in this case Humans are able to easily judge if a concepts are related to each other, there for is a problem when Student use a synonym words during the answer in case they forget the target answer and they use their alternative words in the answer which will be different from the Model answer that prepared by the structure. The Standard text similarity measures perform poorly on such tasks. Short answer only provides a limited content, because the length of the text is typically short, ranging from a single word to a dozen words. This research has two propose; the first propose is Alternative Sentence Generator Method in order to generate the alternative model answer by connecting the method with the synonym dictionary. The second proposed three algorithms combined together in matching phase, Commons Words (COW), Longest Common Subsequence (LCS) and Semantic Distance (SD), these algorithms have been successfully used in many Natural Language Processing systems and have yielded efficient results. The system was manually tested on 40 questions answered by three students and evaluated by teacher in class. The proposed system has yielded %82 correlation-style with human grading, which has made the system significantly better than the other state of the art systems.
The measurement of the relatedness of word semantics based on complementary Wikipedia and WordNet... more The measurement of the relatedness of word semantics based on complementary Wikipedia and WordNet-based methods takes two forms, combined and integrative, which are aimed at increasing the semantic space between related words. However, each form has its own set of issues regarding its components and the strategy that is used to combine and integrate corpus-based and knowledge-based methods. In the integrative strategy, a large corpus, such as Wikipedia, is used to extract a set of related words for a particular concept as a basis for searching the WordNet space. The drawback to this strategy is in its use of a fixed scaling parameter, which only fits an implemented dataset that is near to a human score. Other corpusbased methods use a cut-off threshold that is determined experimentally to reduce the semantic space and to increase the search for a more accurate semantic space. Such methods merely take into account the frequency of bigrams, while ignoring the frequency of individual terms. Knowledge-based methods using a gloss overlap have a similar limitation to the corpus-based methods, where they lead to the loss of many valuable relatedness features that determine a more accurate measurement. Thus, in this paper, a new Information Content Glossary Relatedness (ICGR) approach was proposed in two steps, namely, an Extended-PMI based on a cut-off density threshold was proposed to extract a Robust Relatedness Vector set (RVS) of a large Wikipedia dataset. Then, a Semantic Structural Information (SSI) method was presented to use the RVS as a fulcrum to define the most relatedness gloss in the WordNet of each gloss and to select the top 5 glosses related to each RVS. The results showed that the proposed approach outperformed the state-of-the-art set, where the Extended-PMI achieved a Spearman's correlation of 0.89 to the human score and the ICGR approach achieved a Spearman's correlation of 0.8 to the human score.
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