Semantic Similarity Text Analytics Solution

Compile and analyze large volumes of textual data from multiple information sources with our semantic analysis. Detect semantic similarities between sentences or documents in multiple languages.

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Semantic Similarity Text Analytics Explained

Semantic similarity is the process of analyzing multiple sentence structures to identify similarities between them. It analyzes how close words are in two sentences along with the likeliness of two sentence structures having similar meaning. One of the widely used applications of semantic similarities are content recommender systems.

BytesViews's advanced semantic similarity solution can analyze large volumes of text data to detect similar sentence structures. Compare various documents to examine how similar their words are with semantic analysis. Extract documents or content with similar meaning and text structures.

Semantic Similarity Text Analytics Technical Specifications

Technical Specification of semantic similarity

The semantic analysis will compile and analyze large quantities of text data. The text with the same words and meaning will be categorized and listed. Upload data directly on the platform or use the dedicated plugins to automate the semantic analysis process. Analyze, identify, and extract similar textual data from a variety of information sources.

How to access BytesView Semantic Similarity Solution

Given below are the steps to access the BytesView semantic similarity API. Compile text data into Excel/CSV file and upload it directly on our platform, or let BytesView do it for you.

  • Scrape non-structured text data from multiple information sources for the semantic similarity solution.
  • Compile the scraped text data in an Excel/CSV file
  • Buy a premium plan and install BytesView plug-ins.
  • You will be able to access all of our features, including the semantic analysis API, after purchasing the premium plan. Enter the API key to activate the plugins.
  • Choose an analytical model to analyze text data or train your own custom semantic analysis model.
  • For more information on Semantic Similarity solutions, go through the video.
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Applications/ Use Cases of Semantic Similarity

Duplicate Document Detection

Detect duplicate documents with ease, reduce labor, and increase efficiency. With our Semantic analysis detect plagiarism even when the sentences/words are moved and modified.

Related Term Generation

Easily identify similar company or product names with Semantic analysis. Analyze competitive product features to examine similarities between products and services offered in the industry.

Bio-medical informatics

Use semantic similarity to develop biomedical ontologies namely gene ontology. Compare genes used in other bio-entries and examine documents related to your research.