Search Results for "sentiment"

Similarity is a Java toolkit for calculating similarity scores between text strings. It provides a collection of algorithms for word similarity, phrase similarity, sentence similarity, paragraph similarity, semantic comparison, sentiment tendency, and approximate word discovery. The project is designed to teach and apply natural language similarity methods while keeping the architecture practical and customizable. It includes approaches such as edit distance, cosine similarity, Euclidean distance, Jaccard similarity, Jaro distance, Jaro-Winkler distance, Manhattan distance, SimHash with Hamming distance, and Sørensen-Dice coefficient. ...

WTF Dial is an example Go web application built around a real-time team sentiment dashboard. The app lets team members report how bad or chaotic things currently feel on a shared percentage dial. Beyond the playful concept, the repository is mainly intended as a learning resource for building full Go applications. It demonstrates clean application structure, domain-focused types, multiple storage implementations, HTTP packages, command packages, and documented design decisions. ...

SentEval is a standardized toolkit for evaluating sentence embeddings across a wide spectrum of downstream tasks and probing tests. It defines a simple interface—provide an encoder function from sentences to vectors—and then runs consistent training/evaluation loops for tasks like sentiment, entailment, paraphrase, and semantic textual similarity. The suite also contains linguistic probing tasks that illuminate what properties embeddings capture, such as tense, word order, or syntactic structure. Datasets are wrapped with unified preprocessing and metrics so results are comparable across papers and implementations. ...

...The sections after that, involve varying levels of difficulty and cover topics as diverse as Machine Learning, Linear Optimization, build systems, command line tools, recommendation engines, Sentiment Analysis and Cloud Computing.

Deeplearning-papernotes is an implementation of Convolutional Neural Networks for sentence and text classification in TensorFlow, based on a well-known research paper that applies CNN architectures to natural language processing tasks with strong performance in sentiment analysis and similar classification problems. The repository provides the complete network definition, including an embedding layer to convert words into dense representations, convolution and max-pooling layers to extract informative features, and a final softmax classifier to distinguish between target classes. It includes data preprocessing helpers, training scripts, and configuration options so developers can experiment with different filter sizes, dropout rates, and hyperparameters to optimize performance for their dataset.

This application was developed by Incentro to satisfy requests by clients for a sentiment analyser for the Dutch language. It is currently in it's alpha stage and we expect to have a beta release by November 2012. If you would like to help with the development or testing of this product please contact us at +31[0]15 76 40 750 - of info {at} incentro.com. Deze applicatie is ontwikkeld door Incentro om te voldoen aan klantaanvragen voor een sentimentanalyse module voor de Nederlandse taal. ...