Dynamic Classification of Sentiments from Restaurant Reviews Using Novel Fuzzy-Encoded LSTM

User reviews on social media have sparked a surge in interest in the application of sentiment analysis to provide feedback to the government, public and commercial sectors. Sentiment analysis, spam identification, sarcasm detection and news classification are just few of the uses of text mining. For many firms, classifying reviews based on user feelings is a significant and collaborative effort. In recent years, machine learning models and handcrafted features have been used to study text classification, however they have failed to produce encouraging results for short text categorization. Deep neural network based Long Short-Term Memory (LSTM) and Fuzzy logic model with incremental learning is suggested in this paper. On the basis of F1-score, accuracy, precision and recall, suggested model was tested on a large dataset of hotel reviews. This study is a categorization analysis of hotel review feelings provided by hotel customers. When word embedding is paired with LSTM, findings show that the suggested model outperforms current best-practice methods, with an accuracy 81.04%, precision 77.81%, recall 80.63% and F1-score 75.44%. The efficiency of the proposed model on any sort of review categorization job is demonstrated by these encouraging findings

Aspect Based Opinion Mining & Sentiment Analysis

Opinion mining is a relatively new field that refers to the practice of collecting feedback in the form of online reviews and ratings left by users on various topics. Researchers are now able to monitor the states of consciousness of individuals in real-time because to this development. Just lately, a number of research papers for sentiment analysis were implemented, each of which was based on a unique categorization and ranking procedure. However, the amount of time necessary for the newline performing class has not decreased in any way. Sentiment Sensitivity newline word list SST was provided as a solution to the problem of function mismatch in the go-domain sentiment class across the source area and the target domain; however, achieving improved accuracy and identifying distributional similarities of words became less effective as time went on. Hidden Markov’s persistent development may be seen at the beginning. Cosine In order to achieve more effective and clean pre-processing, a method that is conceptually quite similar to HM-CPCS has been devised. The HM-CPCS methodology, which has recently been suggested, makes use of the POS tagger, a variant of which is based on the Hidden Markov algorithm. Evaluations are created using data from a wide variety of different domains. Similar to a newline, the tags that come before and after it compute the possibility of transitions and the existence of the term newline among the tags in order to increase capability. This is done in order to improve capability

On the strike bt seafood exporters at Visakhapatnam fisheries harbour in Andhra Pradesh

Visakhapatnam Fisheries Harbour Is one of the major fisheries harbours in India. Every day about 275 to 300 small mechanised boats, 150 to 175 Sona boats and 150 to 200 Mini and Mexican trawlers go out for fishing from this harbour. About 300 to 350 fish traders including local fisherwomen depend completely on this fish business for their livelihood. Each trader gets atleast Rs. 200/- per day

Combined Effect of Soret Effect and Temperature Dependent Heat Sources on Hydromagnetic Convective Heat and Mass Flow Through A Porous Medium in A Porous Cylindrical Annulus

ABSTRACT In this paper, we analyze Soret effect on the natural convective heat and mass transfer in a fluid saturated porous medium confined in a porous vertical cylindrical annulus, under the influence of a radial magnetic field. The flow is subjected to the presence of temperature dependent heat generating source. The zeroth and first order perturbation equations obtained by using asymptotic expansion with respect to suction parameter are solved numerically by finite difference technique

An Insilco Approach to Restrain HIV Replication Through Clustering and Virtual Screening

Abstract Human Immunodeficiency Virus (HIV) type-1 non-nucleoside and nucleoside reverse transcriptase inhibitors (NNRTIs) are key drugs to inhibit replication of virus, we have used virtual screening and docking resulted in inhibit replication effectively at active binding site, 884 ligands were extracted and docking analysis resulted in 59 best molecules further by clustering analysis have paved the way for innovative drug design which is better than existing nevirapine ,top three molecules (ZINC04923148, ZINC05442451 and ZINC04923002) were reported as possible novel HIV-RT inhibitors

Interception of Peanut Stripe Virus in Soybean Seeds Imported from China

Investigations suggested that soyabean seeds, and the seeds of potential hosts of peanut stripe potyvirus imported to India from China, should be tested for the virus in quarantine

Survey for Peanut Stripe Virus in India

This virus, not previously reported from India, was identified on the basis of symptoms on groundnut and Chenopodium amaranticolor and serological tests in some of the entries in an initial evaluation trial obtained from NRGC or GAU, Junagadh. Efforts are being made to determine the original source of infested seed

BOBMEX: the Bay of Bengal monsoon experiment

The first observational experiment under the Indian Climate Research Programme, called the Bay of Bengal Monsoon Experiment (BOBMEX), was carried out during July-August 1999. BOBMEX was aimed at measurements of important variables of the atmosphere, ocean, and their interface to gain deeper insight into some of the processes that govern the variability of organized convection over the bay. Simultaneous time series observations were carried out in the northern and southern Bay of Bengal from ships and moored buoys. About 80 scientists from 15 different institutions in India collaborated during BOBMEX to make observations in most-hostile conditions of the raging monsoon. In this paper, the objectives and the design of BOBMEX are described and some initial results presented. During the BOBMEX field phase there were several active spells of convection over the bay, separated by weak spells. Observation with high-resolution radiosondes, launched for the first time over the northern bay, showed that the magnitudes of the convective available potential energy (CAPE) and the convective inhibition energy were comparable to those for the atmosphere over the west Pacific warm pool. CAPE decreased by 2-3 kJ kg-1 following convection, and recovered in a time period of 1-2 days. The surface wind speed was generally higher than 8 m s-1. The thermohaline structure as well as its time evolution during the BOBMEX field phase were found to be different in the northern bay than in the southern bay. Over both the regions, the SST decreased during rain events and increased in cloud-free conditions. Over the season as a whole, the upper-layer salinity decreased for the north bay and increased for the south bay. The variation in SST during 1999 was found to be of smaller amplitude than in 1998. Further analysis of the surface fluxes and currents is expected to give insight into the nature of coupling

Electrochemical and lithium-ion transport properties of layered Li-rich Li1.10(Ni0.32X0.01Co0.33Mn0.33)O2 (X = Dy/Gd/Ho) positive electrodes

864-876Layer structured Li1.10(Ni0.32X0.01Co0.33Mn0.33)O2 (X = Dy/Gd/Ho) compounds were synthesized via the microwave assisted solvothermal route. The impacts of doping on the electrical and electrochemical properties of Li1.10 (Ni0.32X0.01Co0.33Mn0.33)O2 compounds were investigated. Rietveld refined XRD pattern showed Li1.10 (Ni0.32X0.01Co0.33Mn0.33)O2 compounds with layered hexagonal structure. SEM images revealed the compounds with micrometer sized grains. The Li1.10 (Ni0.33Co0.33Mn0.33)O2 compound delivered an initial discharge capacity of 197 mAh/g at 0.2C and retained a capacity of 163mAh/g after 50th cycle in the voltage window of 2.5-4.6V. The cycling stability of Li1.10(Ni0.33Co0.33Mn0.33)O2 compound was improved with rare earth doping. Li1.10(Ni0.32Dy0.01Co0.33Mn0.33)O2 compound delivered the discharge capacity of 166 mAh/g after50th cycle in the potential window 2.5-4.6V at 0.2C with 100% capacity retention. AC impedance studies displayed the electrical conductivity in the order of 10-6 S/cm. Wagner polarization analysis revealed the improvement in electronic transference number via rare earth doping