數位資產管理

Azure

此架構描述知識挖掘的數位資產管理。This architecture describes digital asset management for knowledge mining.

由於每天建立的非結構化資料量,許多公司都不會在其檔案內利用或尋找資訊。Given the amount of unstructured data created daily, many companies are struggling to make use of or find information within their files. 透過搜尋索引的知識挖掘,讓終端客戶和員工可以輕鬆地找到他們所要尋找的內容。Knowledge mining through a search index makes it easy for end customers and employees to locate what they are looking for faster.

架構圖

資料流程Data Flow

有三個步驟:內嵌、擴充和探索。There are three steps: Ingest, Enrich and Exploration. 首先,非結構化和結構化資料會內嵌,然後使用 AI 擴充這項資料,並透過搜尋、現有的商務應用程式或分析解決方案,找出並探索新的結構化資料。First, the unstructured and structured data is ingested then enrichment of this data with AI to extract information and find and finally explore the newly structured data via search, existing business applications or analytics solutions.

  1. 使用者可以內嵌不同類型的技術內容,例如文章和影像封存、相片和影片、內部檔、行銷資產、宣傳冊The user can ingest different types of technical content like article and image archives, photos and videos, internal documents, marketing assets, brochures
  2. 這項內容是透過使用自動影像字幕和使用電腦視覺、名人辨識、語言翻譯和實體辨識的物件偵測來擴充This content is enriched by using automatic image captioning and object detection with computer vision, celebrity recognition, language translation, and entity recognition
  3. 最後,使用者可以將搜尋索引整合至網站。And finally, the user can integrate the search index into a website.

元件Components

用來執行技術內容審查和研究工具的主要技術Key technologies used to implement tools for technical content review and research

後續步驟Next steps

使用 知識挖掘解決方案加速器 ,建立具有 Azure 認知搜尋的初始知識挖掘原型。Using the knowledge mining solution accelerator to build an initial knowledge mining prototype with Azure Cognitive Search.

使用 Microsoft 的自訂 WEB API建立自訂技能Building custom skills with Microsoft's Custom Web API