Papers by Udaya Raj Dhungana
International Journal of Applied Power Engineering (IJAPE)
Energy fraud in the distribution sector of electric utility includes electricity theft, meter tam... more Energy fraud in the distribution sector of electric utility includes electricity theft, meter tampering, or billing error. This fraud causing non-technical loss has led to an economic loss of the company. In order to detect and minimize fraud, different technologies have been used. From conventional methods to development in the field of artificial intelligence (AI), effective and reliable fraud detection methods have been proposed. This paper first provides an overview of different proposed methods for non-technical loss detection and evaluate the advantage and limitation of using those methods. Furthermore, several supervised and unsupervised machine learning methods for detecting electricity theft are discussed in summary along with their metrics and attributes used. Finally, these methods are classified based on the overall operation and the parameters used. This paper provides comparisons of several fraud detection methods using AI along with their weak and strong points and th...
PolyWordNet: A lexical database
2016 International Conference on Inventive Computation Technologies (ICICT), 2016
We developed a new lexical database named as ‘PolyWordNet’. The PolyWordNet organizes multiple se... more We developed a new lexical database named as ‘PolyWordNet’. The PolyWordNet organizes multiple senses of a polysemy word in such a way that each sense of the polysemy word is linked with its related words by dividing these related words into verbs, nouns, adverbs and adjectives. Each related word in the PolyWordNet is linked only with a single sense of a polysemy word except for the case of bridging related word. This is because such related word will lead to the multiple senses of a polysemy word during the sense disambiguation process if the related word is liked to more than one sense of the same polysemy word introducing the ambiguity in ambiguity as in the case of contextual overlap count WSD approaches that use the Princeton WordNet for sense disambiguation. The PolyWordNet resolves this problem which is produced due to the common information collected from Princeton WordNet. The results obtained from the experiments show exceptionally high accuracy (96.11%) of our Word Sense Disambiguation algorithm that uses our lexical database PolyWordNet. This accuracy is significantly higher than that of the accuracy (58.33%) of the other contextual overlap count Word Sense Disambiguation method that used the Princeton WordNet for sense disambiguation.
PolyWordNet is a new lexical database which deals with the organization of senses of polysemy wor... more PolyWordNet is a new lexical database which deals with the organization of senses of polysemy words. It mimics the way how human mind organizes the senses of polysemy words and their related words to analyze and determine correct meaning of a polysemy word in a context. A related word of a sense of a polysemy word is a word which provides necessary and sufficient context to disambiguate the meaning of the polysemy word. A context with a polysemy word must contain at least one related word that determines the correct sense of the polysemy word. The PolyWordNet utilizes this fact to organize the senses of a polysemy word with their corresponding related words. PolyWordNet is completely different than that of the dictionary and WordNet. The words which spell similar come together in dictionary. The words with similar meaning come together in WordNet. The same words, in WordNet, are connected to the multiple senses of the same polysemy word. This introduces an ambiguity. This ambiguity ...
Word sense disambiguation using PolyWordNet
2016 International Conference on Inventive Computation Technologies (ICICT), 2016
Hypernymy in WordNet, Its Role in WSD, and Its Limitations
2015 7th International Conference on Computational Intelligence, Communication Systems and Networks, 2015
This paper presents a new model of WordNet that is used to disambiguate the correct sense of poly... more This paper presents a new model of WordNet that is used to disambiguate the correct sense of polysemy word based on the clue words. The related words for each sense of a polysemy word as well as single sense word are referred to as the clue words. The conventional WordNet organizes nouns, verbs, adjectives and adverbs together into sets of synonyms called synsets each expressing a different concept. In contrast to the structure of WordNet, we developed a new model of WordNet that organizes the different senses of polysemy words as well as the single sense words based on the clue words. These clue words for each sense of a polysemy word as well as for single sense word are used to disambiguate the correct meaning of the polysemy word in the given context using knowledge based Word Sense Disambiguation (WSD) algorithms. The clue word can be a noun, verb, adjective or adverb.
KEYWORDS
Word Sense Disambiguation, WordNet, Polysemy Words, Synset, Hypernymy, Context word, Clue Words
Word sense disambiguation in Nepali language
2014 Fourth International Conference on Digital Information and Communication Technology and its Applications (DICTAP), 2014
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Papers by Udaya Raj Dhungana
KEYWORDS
Word Sense Disambiguation, WordNet, Polysemy Words, Synset, Hypernymy, Context word, Clue Words