Semantic Search Engine

BIGDATA SUITE

Semantic Search Engine Discovery

It is an intelligent semantic search engine (DISCOVERY) in which an AI-based search engine using machine learning and deep learning understands the meaning of words and documents. By learning the feature of data through data collection by applying machine learning algorithm which could perform Feature Learning, it provides enhanced search performance and search results in users’ preference.

It is also a semantic search solution that allows the machine to understand the meaning of words and documents. It even has the built-in Deep Search function that identifies the meaning of the entered keyword by itself to search.

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< Intelligent Semantic Search engine concept map >

The storage used by Big Data Suite is basically a big data storage (GFS-GLORY-FS) where parallel or distributed storage is possible. Large distributed file systems should have the following: cost-effectiveness, accommodating ever-increasing data, dealing with frequently occurring failures, ease of management, rapid I / O performance, optimal data placement, effective cache usage, flexible response to load concentration, Security, etc. These are basically included in our system.

Main Features

Main features of Intelligent Semantic Search engine

Its feature learning involves not only large amounts of DB distributed within the enterprise, but also large-capacity big data such as external social big data, sensor and log data, and office documents such as DOC, PPT, XLS, and HWP. It is an intelligent big data semantic-based search engine with maximum search efficiency and exceptional search quality performance.

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Main features of big data storage

It is a distributed file system that can be used to build storage space using thousands to tens of thousands of low-cost servers and which could process large data with efficient failure control capabilities and high I / O processing performance. GFS has the following main features.

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   Main features and specifications

It provides the users with various systems and various search functions by building an efficient connection service through providing search service interface feature with development convenience and standardized data processing of the search services.

  • Real-time parallel distributed index and various building environment support (internal features of the engine)
  • Large-capacity parallel distributed search processing feature (internal features of the engine)
  • Intelligent search feature
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  • Various language processing features
  • Manager feature
  • Bigdata storage feature
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Main engine screen

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