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Text Sentiment Analysis Using Frequency-Based Vigorous Features

China Communications 2019年第12期16卷 145-153页

作者： Abdul Razzaq Muhammad Asim Zulqrnain Ali Salman Qadri Imran Mumtaz Dost Muhammad Khan qasim niaz Department of Computer Science MNS-University of AgricultureMultan60600Pakistan University of Management and Technology(UMT) Lahore54000Pakistan NFC Institute of Engineering&Technology Multan60600Pakistan Department of CS&IT The Islamia University of Bahawalpur63100Pakistan Computer Science Department University of AgricultureFaisalabad38000Pakistan Department of Computer Science Institute of Southern PunjabMultan60600Pakistan

Sentiment Analysis, an un-abating research area in text mining, requires a computational method for extracting useful information from text. In recent days, social media has become a really rich source to get information about the behavioral state of people(opinion) through reviews and comments. Numerous techniques have been aimed to analyze the sentiment of the text, however, they were unable to come up to the complexity of the sentiments. The complexity requires novel approach for deep analysis of sentiments for more accurate prediction. This research presents a three-step Sentiment Analysis and Prediction(SAP) solution of Text Trend through K-Nearest Neighbor(KNN). At first, sentences are transformed into tokens and stop words are removed. Secondly, polarity of the sentence, paragraph and text is calculated through contributing weighted words, intensity clauses and sentiment shifters. The resulting features extracted in this step played significant role to improve the results. Finally, the trend of the input text has been predicted using KNN classifier based on extracted features. The training and testing of the model has been performed on publically available datasets of twitter and movie reviews. Experiments results illustrated the satisfactory improvement as compared to existing solutions. In addition, GUI(Hello World) based text analysis framework has been designed to perform the text analytics.

关键词： text mining sentiment analysis sentiment shifters KNN

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First report on molecular characterization of Leishmania species from cutaneous leishmaniasis patients in southern Khyber Pakhtunkhwa province of Pakistan

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Asian Pacific Journal of Tropical Medicine 2017年第7期10卷 785-788页

作者： Mubbashir Hussain Shahzad Munir Sultan Ayaz Bahar Ullah Khattak Taj Ali Khan niaz Muhammad Muhammad Anees Hazir Rahman Muhammad qasim Muhammad Ameen Jamal Irfan Ahmed Kashif Rahim Humaira Mazhar Noha Watanay Mohamed Kasbari Vector Borne Diseases Laboratory Department of MicrobiologyKohat University of Science and Technology Kohat Department of Plant Pathology Faculty of Plant ProtectionYunnan Agricultural University College of Animal Husbandry and Veterinary Sciences Abdul Wali Khan University Mardan College of Animal Science and Technology Yunnan Agricultural University Yunnan Provincial Key Laboratory of Animal Nutrition and Feed Yunnan Agricultural University Beijing Key Laboratory of Genetic Engineering Drug and Biotechnology Institute of Biochemistry and BiotechnologyCollege of Life SciencesBeijing Normal University US Naval Medical Research Unit-3 (NAMRU 3) ANSES Animal Health Laboratory

Objective: To report presence of Leishmania major in Khyber Pakhtunkhwa of Pakistan, where cutaneous leishmaniasis(CL) is endemic and was thought to be caused by Leishmania tropica only. Methods: Biopsy samples from 432 CL suspected patients were collected from 3 southern districts of Khyber Pakhtunkhwa during years 2011–2016. Microscopy on Giemsa stained slides were done followed by amplification of the ribosomal internal transcribed spacer 1 gene. Results: Leishmania amastigotes were detected by microscopy in 308 of 432 samples(71.3%) while 374 out of 432 samples(86.6%) were positive by ribosomal internal transcribed spacer 1 PCR. Subsequent restriction fragment length polymorphism confirmed Leishmania tropica in 351 and Leishmania major in 6 biopsy samples. Conclusions: This study is the first molecular characterization of Leishmania species in southern Khyber Pakhtunkhwa. It confirmed the previous assumptions that anthroponotic CL is the major CL form present in Khyber Pakhtunkhwa province. Furthermore, this is the first report of Leishmania major from a classical anthroponotic CL endemic focus identified in rural areas of Kohat district in southern Khyber Pakhtunkhwa.

关键词： Cutaneous leishmaniasis ITS-PCR RFLP Leishmania tropica Khyber Pakhtunkhwa

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