Search Results for "wordnet-based semantic similarity measurement"
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Showing 14 open source projects for "wordnet-based semantic similarity measurement"
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Whether natural disaster, cyberattack, or plain-old human error, data can disappear in the blink of an eye. ConnectWise BCDR (formerly Recover) delivers reliable and secure backup and disaster recovery backed by powerful automation and a 24/7 NOC to get your clients back to work in minutes, not days.
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With the world of work changed forever, it’s essential to manage your workplace and assets together to effectively create a high-performing environment. The Eptura experience combines the power of workplace management software with asset management, enabling you to effectively operate your building and facilitate hybrid work.
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SentenceTransformers
Multilingual sentence & image embeddings with BERT
SentenceTransformers is a Python framework for state-of-the-art sentence, text and image embeddings. The initial work is described in our paper Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. You can use this framework to compute sentence / text embeddings for more than 100 languages. These embeddings can then be compared e.g. with cosine-similarity to find sentences with a similar meaning. This can be useful for semantic textual similar, semantic search, or paraphrase mining... -
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Vector AI
A platform for building vector based applications
Vector AI is a framework designed to make the process of building production-grade vector-based applications as quick and easily as possible. Create, store, manipulate, search and analyze vectors alongside json documents to power applications such as neural search, semantic search, personalized recommendations etc. Image2Vec, Audio2Vec, etc (Any data can be turned into vectors through machine learning). Store your vectors alongside documents without having to do a db lookup for metadata about... -
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UFO-Cytoscape
Ontology-based semantic similarity calculation and visualization
Motivation: Biomedical ontologies have been growing quickly and proven to be useful in many biomedical applications. The use of this data is mainly based on semantic similarity calculation between ontology terms and between annotated biomedical entities. Many semantic similarity measures have been proposed for such calculation. Results: A number of tools have been developed on different platforms for ontology visualization and semantic similarity calculation. However, these tools have... -
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This is a Python-based efficient implementation of several semantic similarity measures. The target is to enable fast and easy calculation of similarity between proteins and genes using the Gene Ontology (GO).
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Java API to Access XML database for Arabic Word Net (AWN) from this page http://www.talp.upc.edu/index.php/technology/resources/multilingual-lexicons-and-machine-translation-resources/multilingual-lexicons/72-awn The API code provides many built-in functions. The Java API code also computes semantic similarity between two Arabic concepts
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UMLS::Query is an umbrella for projects that create measures of semantic similarity for the biomedical domain. Our current project is UMLS-Interface and UMLS-Similarity. Our JBI-2007 article was based on Semantic-Similarity and Snomed-Interface.
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This package consists of Perl modules that implement the semantic relatedness measures of Leacock-Chodorow (1998), Jiang-Conrath (1997), Resnik (1995), Lin (1998), Hirst-St-Onge (1998), Wu & Palmer (1994), Banerjee-Pedersen (2002), and Patwardhan (2003).
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Calculate Semantic Similarity
Calculate Semantic Similarity between the Sentences
FOR A SIMPLER SOLUTION, PLEASE VISIT MY NEW PROJECT: https://sourceforge.net/projects/mechaglot/ This program is made to find the semantic similarities between the sentences, according to categories of their words. It is an enhancement of the Vector-Space analysis found withing the Classifier4j, which does not take into account the semantic meanings of the words. Furthermore, the Vector-Space analysis of the Classifier4J does not work well with the short sentences, while this enhancement... -
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SAWA calculates a semantic similarity coefficient between two sentences. Coefficient is expressed between "0" and "1", where: 0 means there is not semantic similarity among them; 1 vice versa.
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ProcureDesk is an integrated purchasing and invoicing platform tailored to help small to medium sized businesses streamline their procurement processes. This user-friendly system automates workflows and consolidates purchasing data into a centralized dashboard, allowing companies to control spending and enhance transparency efficiently. Features like automated invoice matching, simple requisition creation, and immediate cash flow insights minimize manual tasks and boost operational efficiency. ProcureDesk is perfect for smaller enterprises leveraging big-business strategies to reduce costs and optimize their purchasing activities. Discover how ProcureDesk can transform your procurement process into a more effective and manageable part of your business.
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HRSS
Hybrid Relative Specificity Similarity based on Gene Ontology
This software provides a hybrid GO-based semantic similarity algorithm for evaluating the functional similarity between GO terms or gene products. The software uses the pre-downloaded GO database files and the GO annotation files. It allows the users to set organisms, and evidence codes ignored. The software is composed of five modules, getGODAG, getGOAnno, hrssmatrix, hrsstps and hrsspps. -
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SIM-DL: Semantic Similarity Measurement Server for concepts (and individuals) represented using (expressive) Description Logics (DL).
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SEALS addresses two key challenges: the creation of a lasting reference infrastructure for semantic technology evaluation and the continuous benchmarking of semantic technologies at a large scale via public worldwide evaluation campaigns.
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go2Sim measures semantic similarity between genes annotated with Gene Ontology terms. Resnik and Wang methods supported. A new improvement of the methods is currently in development, it will be available as soon as the results have been published.
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