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236 results on '"Abulaish, Muhammad"'

1. Efficient Subgraph Isomorphism Finding in Large Graphs using Eccentricity and Limiting Recursive Calls

Author

Ansari, Zubair Ali, Abulaish, Muhammad, Thoker, Irfan Rashid, and Jahiruddin

Subjects
Computer Science - Databases
Abstract

The subgraph isomorphism finding problem is a well-studied problem in the field of computer science and graph theory, and it aims to enumerate all instances of a query graph in the respective data graph. In this paper, we propose an efficient method, SubISO, to find subgraph isomorphisms using an objective function, which exploits some isomorphic invariants and eccentricity of the query graph's vertices. The proposed objective function is used to determine pivot vertex, which minimizes both number and size of the candidate regions in the data graph. SubISO also limits the maximum recursive calls of the generic SubgraphSearch function to deal with straggler queries for which most of the existing algorithms show exponential behaviour. The proposed approach is evaluated over three benchmark datasets. It is also compared with three well known subgraph isomorphism finding algorithms in terms of execution time, number of identified embeddings, and ability to deal with the straggler queries, and it performs significantly better.

Published
2023

2. A Comprehensive Empirical Evaluation of Existing Word Embedding Approaches

Author

Zaland, Obaidullah, Abulaish, Muhammad, and Fazil, Mohd.

Subjects
Computer Science - Computation and Language, Computer Science - Neural and Evolutionary Computing
Abstract

Vector-based word representations help countless Natural Language Processing (NLP) tasks capture the language's semantic and syntactic regularities. In this paper, we present the characteristics of existing word embedding approaches and analyze them with regard to many classification tasks. We categorize the methods into two main groups - Traditional approaches mostly use matrix factorization to produce word representations, and they are not able to capture the semantic and syntactic regularities of the language very well. On the other hand, Neural-network-based approaches can capture sophisticated regularities of the language and preserve the word relationships in the generated word representations. We report experimental results on multiple classification tasks and highlight the scenarios where one approach performs better than the rest., Comment: 28 pages, 3 figures and 10 tables

Published
2023

5. An Unseen Features-Enriched Lifelong Machine Learning Framework

Author

Wasi, Nesar Ahmad, Abulaish, Muhammad, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Gervasi, Osvaldo, editor, Murgante, Beniamino, editor, Taniar, David, editor, Apduhan, Bernady O., editor, Braga, Ana Cristina, editor, Garau, Chiara, editor, and Stratigea, Anastasia, editor

Published
2023
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7. A Novel Weighted Distance Measure for Multi-Attributed Graph

Author

Abulaish, Muhammad and Jahiruddin

Subjects
Computer Science - Social and Information Networks, Computer Science - Artificial Intelligence, Computer Science - Data Structures and Algorithms, Computer Science - Information Retrieval
Abstract

Due to exponential growth of complex data, graph structure has become increasingly important to model various entities and their interactions, with many interesting applications including, bioinformatics, social network analysis, etc. Depending on the complexity of the data, the underlying graph model can be a simple directed/undirected and/or weighted/un-weighted graph to a complex graph (aka multi-attributed graph) where vertices and edges are labelled with multi-dimensional vectors. In this paper, we present a novel weighted distance measure based on weighted Euclidean norm which is defined as a function of both vertex and edge attributes, and it can be used for various graph analysis tasks including classification and cluster analysis. The proposed distance measure has flexibility to increase/decrease the weightage of edge labels while calculating the distance between vertex-pairs. We have also proposed a MAGDist algorithm, which reads multi-attributed graph stored in CSV files containing the list of vertex vectors and edge vectors, and calculates the distance between each vertex-pair using the proposed weighted distance measure. Finally, we have proposed a multi-attributed similarity graph generation algorithm, MAGSim, which reads the output of MAGDist algorithm and generates a similarity graph that can be analysed using classification and clustering algorithms. The significance and accuracy of the proposed distance measure and algorithms is evaluated on Iris and Twitter data sets, and it is found that the similarity graph generated by our proposed method yields better clustering results than the existing similarity graph generation methods.

Published
2018

10. Self-deprecating Humor Detection: A Machine Learning Approach

Author

Kamal, Ashraf, Abulaish, Muhammad, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Nguyen, Le-Minh, editor, Phan, Xuan-Hieu, editor, Hasida, Kôiti, editor, and Tojo, Satoshi, editor

Published
2020
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11. A Contextual Semantic-Based Approach for Domain-Centric Lexicon Expansion

Author

Abulaish, Muhammad, Fazil, Mohd, Anwar, Tarique, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Borovica-Gajic, Renata, editor, Qi, Jianzhong, editor, and Wang, Weiqing, editor

Published
2020
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12. Skull stripping on multimodal brain MRI scans using thresholding and morphology.

Author

Bhat, Sajid Y., Naqshbandi, Afnan, and Abulaish, Muhammad

Subjects
SKULL, BRAIN imaging, MORPHOLOGY, IMAGE processing, MAGNETIC resonance imaging
Abstract

This paper introduces a novel thresholding and morphology-based skull stripping method for different MRI modalities. The proposed method is designed in a way which is easy to use and generates satisfactory results with minimal parameter adjustments. The method is evaluated on three different benchmark datasets and compared with nine state-of-the-art skull stripping methods. The experimental results suggest that the proposed method generates comparable results to some of the best methods in literature. However, unlike many other methods, it works well on different types of MRI scans. Moreover, this method generates the skull mask along with the brain mask that can be used to study various skull pathologies. [ABSTRACT FROM AUTHOR]

Published
2024
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16. The role of lifelong machine learning in bridging the gap between human and machine learning: A scientometric analysis.

Author

Abulaish, Muhammad, Wasi, Nesar Ahmad, and Sharma, Shachi

Subjects
*LEARNING, *BRAIN anatomy, *PROBLEM solving, *COGNITION, *HUMAN experimentation, *MACHINE learning, *BRIDGES
Abstract

Due to advancements in data collection, storage, and processing techniques, machine learning has become a thriving and dominant paradigm. However, one of its main shortcomings is that the classical machine learning paradigm acts in isolation without utilizing the knowledge gained through learning from related tasks in the past. To circumvent this, the concept of Lifelong Machine Learning (LML) has been proposed, with the goal of mimicking how humans learn and acquire cognition. Human learning research has revealed that the brain connects previously learned information while learning new information from a single or small number of examples. Similarly, an LML system continually learns by storing and applying acquired information. Starting with an analysis of how the human brain learns, this paper shows that the LML framework shares a functional structure with the brain when it comes to solving new problems using previously learned information. It also provides a description of the LML framework, emphasizing its similarities to human brain learning. It also provides citation graph generation and scientometric analysis algorithms for the LML literatures, including information about the datasets and evaluation metrics that have been used in the empirical evaluation of LML systems. Finally, it presents outstanding issues and possible future research directions in the field of LML. [ABSTRACT FROM AUTHOR]

Published
2024
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27. The Dark Crypto World!

Author

Abulaish, Muhammad and Dalal, Harshita

Abstract

Throughout the annals of history, governments and their central banks have been alleged to breach trust through the manipulation of funds and the debasement of fiat currencies. Cryptocurrencies, with their underpinning blockchain technology, have revolutionized and democratized the modern finance ecosystem. Their digital, decentralized, and unregulated nature has catalyzed a paradigm shift, disrupting the conventional banking system and empowering individuals with direct and absolute control over their assets. Concurrently, cryptocurrencies can be extremely arduous to wrap one’s head around, especially when shrouded with an intricate web of technobabble and algorithmic complexities. The realm of cryptocurrencies, akin to diverse social media platforms, presents a plethora of formidable challenges and inherent dangers. With the incessant advent of new cryptocurrencies, the proliferation of illicit activities has become rampant, posing a grave threat to the crypto community. Crypto trading/investing entails a high-risk endeavor that could jeopardize the entire investment. This article demystifies the underlying perils that engulf the crypto world.

Published
2024
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29. Modeling a Web Forum Ecosystem into an Enriched Social Graph

Author

Anwar, Tarique, Abulaish, Muhammad, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Atzmueller, Martin, editor, Chin, Alvin, editor, Helic, Denis, editor, and Hotho, Andreas, editor

Published
2013
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30. Identification of Sybil Communities Generating Context-Aware Spam on Online Social Networks

Author

Ahmed, Faraz, Abulaish, Muhammad, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Ishikawa, Yoshiharu, editor, Li, Jianzhong, editor, Wang, Wei, editor, Zhang, Rui, editor, and Zhang, Wenjie, editor

Published
2013
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36. A Data Mining Framework for Securing 3G Core Network from GTP Fuzzing Attacks

Author

Ahmed, Faraz, Rafique, M. Zubair, Abulaish, Muhammad, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Jajodia, Sushil, editor, and Mazumdar, Chandan, editor

Published
2011
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37. Classifier Ensembles Using Structural Features For Spammer Detection In Online Social Networks

Author

Abulaish Muhammad and Bhat Sajid Y.

Subjects
social network security, spammer detection, ensemble learning, classifier ensembles, feature extraction, Electronic computers. Computer science, QA75.5-76.95
Abstract

As the online social network technology is gaining all time high popularity and usage, the malicious behavior and attacks of spammers are getting smarter and difficult to track. The newer spamming approaches using the social engineering concepts are making traditional spam and spammer detection techniques obsolete. Especially, content-based filtering of spam messages and spammer profiles in online social networks is becoming difficult. Newer approaches for spammer detection using topological features are gaining attention. Further, the evaluation of ensemble classifiers for detection of spammers over social networking behavior-based features is still in its infancy. In this paper, we present an ensemble learning method for online social network security by evaluating the performance of some basic ensemble classifiers over novel community-based social networking features of legitimate users and spammers in online social networks. The proposed method aims to identify topological and community-based features from users’ interaction network and uses popular classifier ensembles – bagging and boosting to identify spammers in online social networks. Experimental evaluation of the proposed method is done over a real-world data set with artificial spammers that follow a behavior as reported in earlier literature. The experimental results reveal that the identified features are highly discriminative to identify spammers in online social networks.

Published
2015
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39. Opinion-Based Imprecise Query Answering

Author

Abulaish, Muhammad, Ahmad, Tanvir, Jahiruddin, Doja, Mohammad Najmud, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Zaki, Mohammed J., editor, Yu, Jeffrey Xu, editor, Ravindran, B., editor, and Pudi, Vikram, editor

Published
2010
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42. A Relation Mining and Visualization Framework for Automated Text Summarization

Author

Abulaish, Muhammad, Jahiruddin, Dey, Lipika, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Chaudhury, Santanu, editor, Mitra, Sushmita, editor, Murthy, C. A., editor, Sastry, P. S., editor, and Pal, Sankar K., editor

Published
2009
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43. Mining Local Association Rules from Temporal Data Set

Author

Mazarbhuiya, Fokrul Alom, Abulaish, Muhammad, Mahanta, Anjana Kakoti, Ahmad, Tanvir, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Chaudhury, Santanu, editor, Mitra, Sushmita, editor, Murthy, C. A., editor, Sastry, P. S., editor, and Pal, Sankar K., editor

Published
2009
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44. Feature and Opinion Mining for Customer Review Summarization

Author

Abulaish, Muhammad, Jahiruddin, Doja, Mohammad Najmud, Ahmad, Tanvir, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Chaudhury, Santanu, editor, Mitra, Sushmita, editor, Murthy, C. A., editor, Sastry, P. S., editor, and Pal, Sankar K., editor

Published
2009
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46. Semantic Integration of Information Through Relation Mining - Application to Bio-medical Text Processing

Author

Dey, Lipika, Abulaish, Muhammad, Goyel, Rohit, Jahiruddin, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Ghosh, Ashish, editor, De, Rajat K., editor, and Pal, Sankar K., editor

Published
2007
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47. Enhancing a Biological Concept Ontology to Fuzzy Relational Ontology with Relations Mined from Text

Author

Dey, Lipika, Abulaish, Muhammad, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Greco, Salvatore, editor, Hata, Yutaka, editor, Hirano, Shoji, editor, Inuiguchi, Masahiro, editor, Miyamoto, Sadaaki, editor, Nguyen, Hung Son, editor, and Słowiński, Roman, editor

Published
2006
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48. Knowledge Enhancement Through Ontology-Guided Text Mining

Author

Abulaish, Muhammad, Dey, Lipika, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Pal, Sankar K., editor, Bandyopadhyay, Sanghamitra, editor, and Biswas, Sambhunath, editor

Published
2005
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49. An Ontology-Based Pattern Mining System for Extracting Information from Biological Texts

Author

Abulaish, Muhammad, Dey, Lipika, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Ślęzak, Dominik, editor, Yao, JingTao, editor, Peters, James F., editor, Ziarko, Wojciech, editor, and Hu, Xiaohua, editor

Published
2005
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50. A Framework for Extending Fuzzy Description Logic to Ontology Based Document Processing

Author

Singh, Shailendra, Dey, Lipika, Abulaish, Muhammad, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Favela, Jesús, editor, Menasalvas, Ernestina, editor, and Chávez, Edgar, editor

Published
2004
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