Rajinder Singh

Bio: Rajinder Singh is an academic researcher from Guru Nanak Dev University. The author has contributed to research in topics: Sentiment analysis & Intramolecular force. The author has an hindex of 14, co-authored 55 publications receiving 586 citations. Previous affiliations of Rajinder Singh include Spanish National Research Council & Autonomous University of Madrid.

Optimization of sentiment analysis using machine learning classifiers

Abstract: Words and phrases bespeak the perspectives of people about products, services, governments and events on social media. Extricating positive or negative polarities from social media text denominates task of sentiment analysis in the field of natural language processing. The exponential growth of demands for business organizations and governments, impel researchers to accomplish their research in sentiment analysis. This paper leverages four state-of-the-art machine learning classifiers viz. Naive Bayes, J48, BFTree and OneR for optimization of sentiment analysis. The experiments are performed using three manually compiled datasets; two of them are captured from Amazon and one dataset is assembled from IMDB movie reviews. The efficacies of these four classification techniques are examined and compared. The Naive Bayes found to be quite fast in learning whereas OneR seems more promising in generating the accuracy of 91.3% in precision, 97% in F-measure and 92.34% in correctly classified instances.

A review of sentiment analysis techniques for opinionated web text

Abstract: Social Media nowadays generate huge loads of data that can be valuable in many contexts. It includes media of all formats by which groups of users interact to generate ideas in a distributed and networked process. Data scientists from Twitter have found that the main reason for attaining fame of Presidential Candidate in the upcoming elections scheduled in Nov, 2016 in US is the reach of social media. Researchers and data scientists can use data on social media to track opinions of people about products and services. Many approaches are working behind the scene to reduce errors in opinion mining and sentiment analysis and to attain a level of accuracy for meeting the growing demands of organizations to evaluate their customers. The way people express their opinions have radically changed in the past few years. This paper explores various techniques of distillation of knowledge from huge amount of unstructured information. Generic features of making use of linguistic patterns in sentiment classification are being explored in this paper. In this study investigation of all opinion extraction techniques to generate positive and negative aspects of data with appropriate feature set can help in reduction of error of misclassification.

Recent advances in Sonogashira reactions

Abstract: The coupling of aryl or vinyl halides with terminal acetylenes catalysed by palladium and other transition metals, commonly termed as Sonogashira cross-coupling reaction, is one of the most important and widely used sp2–sp carbon–carbon bond formation reactions in organic synthesis, frequently employed in the synthesis of natural products, biologically active molecules, heterocycles, molecular electronics, dendrimers and conjugated polymers or nanostructures. This critical review focuses on developments in the Sonogashira reaction achieved in recent years concerning catalysts, reaction conditions and substrates (352 references).

Photochemical Reactions as Key Steps in Organic Synthesis

Abstract: 2.3. [4 + 4] Cycloadditions 1058 2.4. Photocycloadditions of Aromatic Compounds 1058 2.4.1. Benzene Derivatives 1058 2.4.2. Condensed Aromatic Compounds 1060 3. Photochemical Rearrangements 1061 4. Cyclizations 1064 4.1. Pericyclizations 1064 4.2. Norrish−Yang Reaction 1066 5. Photochemical Extrusion of Small Molecules 1067 6. Photochemical Electron Transfer 1068 6.1. Photochemical Electron-Transfer Reactions with a Catalytic Sensitizer 1068

Asymmetric construction of stereogenic carbon centers featuring a trifluoromethyl group from prochiral trifluoromethylated substrates.

Abstract: Department of Chemistry, Tianjin University, Tianjin 300072, China; Department of Applied Chemistry, China Agricultural University, Beijing 100193, China; UMR 6014 CNRS, Laboratoire COBRA de l’IRCOF, Université et INSA de Rouen, Rue Tesniere, F-76130 Mont Saint Aignan, France; and Key Laboratory of Organofluorine Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Science, Shanghai 200032, China