Many scientists present web matedata in order to slove the problem . web metadata can transform unstructured data into structural data 為了解決這個問題,很多研究者提出了為web數據建立元數據,可將非結構化數據變成結構化或半結構化數據。
This class also requires reading primary research papers and review papers , viewing structural data with molecular graphics programs , and thinking critically about modern topics in biochemistry 本課程同樣要求閱讀一些初級的研究論文和評論文章,用分子圖像影像程序觀看分子結構,以及批判性地思考當代生物化學的主題。
The traditional approaches to handle non - trivial data structures are either abstracting them from system models or expanding them into non - structural data , which often reduces the efficiency of verification substantively 以往處理復雜數據結構的做法是抽象掉數據信息或者將復雜數據結構打散,因而較大的影響了檢測效率。
To collect structural data and conform the information through existing technology and find out the relation between data through data excavation , we can offer search results that are exacter and more intelligent 通過我們已有的技術對結構化數據的提取和信息整合,用數據挖掘的方法找出數據間的聯系,我們可以提供更準確更智能化的搜索結果。
We can divide web data into two kinds : structural data and unstructured data . we have maturer methords to deal with structural data . however , because traditional database bottom can not deal with unstructured data , a wey that deal with unstructured data need be presented 對于結構化的web數據,已經有較為成熟的解決方法;而對于非結構化的web數據,由于傳統(tǒng)數據庫的底層問題,不能用來處理非結構化數據,迫切希望能提出一種方法進行非結構化數據的處理。