Baidu Natural Language Processing

Baidu Language and Knowledge, based on Baidu’s immense data accumulation, is devoted to developing cutting-edge natural language processing and knowledge graph technologies. Natural Language Processing has open several core abilities and solutions, including more than ten kinds of abilities such as sentiment analysis, address recognition, and customer comments analysis.
Baidu Natural Language Processing
  • Basic Technology
  • Application Technology
  • Application Scenarios
  • Special Advantages
  • Relevant Recommendations

Basic Technology for Language Processing

  • Lexical Analysis

    Based on the word segmentation, part-of-speech tagging, and named entity recognition technology, Lexical Analysis allows you to locate basic language elements, get rid of ambiguity, and support accurate understanding.

  • Word Vector Representation

    Word Vector Representation can calculate texts through vectorization of words. Thus, it can help you quickly complete semantic mining, similarity calculation, and other applications.

  • Semantic Similarity

    Based on deep neural network and massive high-quality data on the internet, Semantic Similarity is possible to calculate the similarity of two words through vectorization of words, meeting the business scenario requirements for high precision.

  • Dependency Syntax Analysis

    Dependency Syntax Analysis can automatically analyze the dependency syntax's structural information in text, achieving accurate understanding of the natural language.

  • DNN Language Model

    DNN language model can judge whether a sentence meets the customs of language expression. Thus, it can help you quickly achieve applications like text analysis, error correction, and smart conversation.

  • Short-text Similarity

    Short-text Similarity provides you with high-precision similarity analysis service for short text. Thus, it can help you achieve applications like recommender system, search engine, and sorting.

Application Technology for Language Processing

  • Text Error-correcting

    Text Error-correcting can identify the text segment containing errors, show errors prompt, and give recommended correct text content.

  • Sentiment Analysis

    Sentiment Analysis performs sentiment judgment for the text containing subjective information. It can also support on-line model training for optimization, Thus it assists you in such applications as word-of-mouth analysis and public opinion analysis.

  • Comment Extraction

    Comment Extraction can extract and analyze comments automatically. Therefore, it helps you accomplish public opinion analysis and user understanding. It also supports product optimization and marketing decision-making.

  • Conversation Emotion Recognition

    It can detect emotional characteristics contained in the user’s daily conversation text. Therefore, it helps enterprises to fully understand the product experience and service quality.

  • Article Tag

    Article Tag can analyze the core keywords of the articles. Therefore, it offers technical support for personalized recommendation, similar article aggregation, and article content analysis.

  • Article Classification

    Article Classification can classify articles in light of their contents. It supports 26 types of contents in fields like entertainment, sports, and technology. It also offers essential supports for such applications as article aggregation and text content analysis.

  • News Digest

    The deep semantic analysis model can extract key information in news and generate news digests with a specified length. It can be used for such scenarios as hot news aggregation, news recommendation, voice broadcast, and APP message push.

  • Address Recognition

    Address Recognition precisely extract names, phone numbers, and address information in the express waybill text. Furthermore, through natural language processing, automatic supplement and correction of address information can also be realized.

Application Scenarios

  • Intelligent Recruitment
  • Intelligent Contract Processing
  • Media Strategy Adoption, Edition, and Review
  • Intelligent Recruitment

    The enterprise recruitment solution includes several application abilities, such as CV resolution, candidate-post match, and talent evaluation. It helps enterprises save the recruitment cost, shorten the recruitment period, and free the HR personnel from the huge daily CVs selection and trivial communication.

    Intelligent Recruitment
  • Intelligent Contract Processing

    Based on such technologies as OCR, Natural Language Processing, and Knowledge Graph, it can offer various application services, including transaction, contract review, and contract archiving and management. It empowers enterprises to conduct contract management and offer legal information services in the whole process, improving the contract review efficiency and accuracy.

    Intelligent Contract Processing
  • Media Strategy Adoption, Edition, and Review

    By relying on such technologies as Natural Language Processing and Knowledge Graph, it can introduce appropriate scenario solutions for the business processes, such as Media Strategy Making, Adoption, Edition, Distribution, Commenting, and Review. Thus, it drives the deep integration between the traditional media and new media in news production, content dissemination, and technical innovation fields.

    Media Strategy Adoption, Edition, and Review

Special Advantages

  • Abundant Capabilities

    Dozens of natural language core algorithms and solutions fully cover various requirements for language processing.

  • Strong Semantic Generalization

    For the standard interface encapsulation, a variety of tools become available rapidly by calling them via cloud computing, reducing the development labor cost significantly.

  • Service Reliability

    The SLA remains stable above 99.99%. It supports hundreds of billions of calling requirements and has complete statistical and monitoring measures.

Relevant Recommendations

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    Based on the abundant data systems for the knowledge graph, it can provide you with a description of the ability of deep comprehension and resolution for entities and concepts in the text semantics.

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    It features one-stop support for intelligent marking, model training, service deployment, and other full-process features. It has abundant built-in pre-training models, which has been widely applied in many fields.

  • Optical Character Recognition

    It offers multi-scenario, multi-language, and high-precision optical character detection and recognition services. Also, it has several ICDAR indexes ranked at the first position worldwide.