Advantages of Iminer Big Data Mining System

  • Massive data, control trends

    Full amount of raw data retention, mass historical data can be tracked

    Full control of the historical data, trends

  • adaptive to change , dynamic analysis

    Free from time and space constraints of the sample survey, at any time in response to customer demand for analysis, rapid access to analysis results

    Free from questionnaires for sample research, flexible customization of various individualized analysis dimensions, all-round display of large data analysis results

  • NLP technique ( natuaral language processing )

    Using artificial intelligence technology and machine learning algorithm, in-depth understanding of text semantics

    Depth mining of the connotation and denotation of customer goals, and deep exploration of the semantic relation between objects, using the techniques of classification, clustering and extraction

    Utilizes a distributed architecture to enable natural language processing algorithms to easily cope with massive amounts of data for efficient analysis

  • Accurate audience analysis

    Demonstrate the interests and concerns of the target audience by modeling their attributes and interests

    Based on the result of social network mining ,Find the opinion leaders and most valuable audience

  • Relevance analysis, insight into business value

    Business brand reputation analysis and audience analysis, explore business value, find business opportunities

    Commercial brand and star, film and television works of large data association analysis, to achieve accurate matching

Big Data Mining Technologies uses a distributed computing architecture to develop algorithms and models for distributed environments that can efficiently process terabytes of data across the entire network, even at the PB level. Class, classification, correlation analysis.

Natural Language Processing (Natural Language Processing) is the use of artificial intelligence algorithms, machine learning model, the computer can in-depth analysis and understanding of the contents of text information, including text information classification, clustering, object recognition, relationship extraction, topic detection .