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Sentence similarity calculation plays an important role in text processing-related research. Many unsupervised techniques such as knowledge-based techniques, corpus-based techniques, string similarity based techniques, and graph alignment techniques are available to measure sentence similarity. However, none of these techniques have been experimented with Tamil. In this paper, we present the first-ever...
Topic models are used in text analysis to extract domain features and to explore unknown domains. The topic models and its extensions follow traditional machine learning approach as single-shot learning. Automatic knowledge based topic models (AKBTM) filled this gap by learning from each task and carrying it to future tasks as knowledge rules. Most of the research in AKBTM focuses on rule extraction...
Intrusion Detection Systems (IDS) are security tools that generate alerts when detecting a malicious activity. The main drawback of IDS is the high number of generated alerts. We propose an approach that integrates the knowledge of several security experts to improve IDS results and reduce the alerts number. The experts' knowledge are expressed in IFO (Instantiated First Order) logic. A new logical...
Patent retrieval is important for technology survey and knowledge protection. Its aim is to search as many patent documents relevant to the patent document query as possible, which is considered as a recall-oriented task. However, existing methods suffer from the term mismatch problem caused by the frequent use of many non-standard technical terminologies in patents. To address the issue, we present...
Semantic relatedness measure play an important roles in Natural Language Processing (NLP) tasks. By using the knowledge bases and current methods, the semantic relatedness measure could be done. This time, we implement the hybrid method in measuring semantic relatedness between the pair of word. Hybrid method is one of the most popular method that used to measures semantic relatedness. Hybrid method...
This paper presents a method to validate the insertion of a new concept in an ontology. This method is based on our previous works which add new concepts in a basic ontology using a general ontology (genaral ontology contains all the concepts of the basic ontology). To verify the semantic relevance of an ontology, we have proposed a method with three steps. First, we have found the neighborhood of...
Evaluating semantic similarity of text document pairs is an active research topic. Various models of document representation have been proposed. Each kind of representation model concentrates on a different kind of information from other kind of models. However, it is difficult for a single model to perform well in all scenarios because of the variety of textual documents. Leveraging these models...
We represent a new framework - Knowledge creation grid for Big data era. Currently, there are various types of data in various fields. The essences of ICT are "scale merit," "scope merit," and "connection merit." The Big data itself represents "scale merit" and "scope merit," because there are massive of data and these data are utilized in various...
Today internet usage has seen tremendous growth. As English is the primary language, documents are mostly available in English language. In India, Hindi is the prevalent language and user wants to access data in Hindi. For the language processing we are required to get the exact sense of polysemous word interpreting the meaning in a particular context. To disambiguate the meaning of the polysemous...
Semantic similarity is an essential component of numerous applications in fields such as natural language processing, artificial intelligence, linguistics, and psychology. Most of the reported work has been done in English. To the best of our knowledge, there is no word similarity measure developed specifically for Arabic. This paper presents a method to measure the semantic similarity between two...
Computer network security is a fashionable and fast-moving field. In the last decade many methodologies and tools have been developed for improving the security of networks and their hosts, but the resources used to deal with the problem often do not yield results commensurate with costs. In the last period the adoption of Network Intrusion Prevention Systems promises to represent an effective line...
Current expectations from nowadays information retrieval systems (IRS) have grown beyond the “document contains these terms” requirement that was considered common sense 10–15 years ago. Nowadays systems are expected to return results that are relevant to the intended meaning of the query. In the general IRS usage scenario, the user is not really interested if the returned documents contain or not...
We research ontological indexing and querying as a solution for getting better results in information retrieval, which translates in getting the most relevant documents meeting a query. While most of the research in this field focuses on query reformulation and document representation methods, we focused our research on an ontology-based query guidance system (our proposed OntoSense engine &...
Similarity between two sentences can be determined by either comparing their commonalities or their differences. Commonalities, which reflect similarity judgment, connect the two sentences while differences, which reflect dissimilarity judgment, represent the unique way of self-identification. Although both of them are essential in determining sentence similarity, however, the existing methods only...
Rule-based approaches (as in our own Kappa, or the BNG language, or many other propositions allowing the consideration of "reaction classes'') offer new and more powerful ways to capture the combinatorial interactions that are typical of molecular biological systems. They afford relatively compact and faithful descriptions of cellular interaction networks despite the combination of two broad...
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