數(shù)鵬通BDA:基于分布式架構(gòu)和人工智能的大數(shù)據(jù)
LinkCM’sBig Data Architecture is delivering the insight to act with speed and conviction; delivering cognitive experience to the masses. AI and deep learning are well implemented with data to transform industries and professions .
數(shù)鵬通(LinkCM)科技正式發(fā)布智能邏輯引擎V3.0,引擎具備強大的自然語言識別NLP和智能邏輯規(guī)則處理SLP功能,自然語言和邏輯判斷是人類智慧的結(jié)晶,相關(guān)領(lǐng)域的研究也是充滿魅力和挑戰(zhàn)的。
LinkCM announced SLE (Smart Forecast Logic Engine) V3.0 recently. SLE V3.0 is enabled by both NLPand SLP,such are fields of interactions between computers and human languages and logics.
數(shù)據(jù)質(zhì)量是模式和算法模型構(gòu)建的基礎(chǔ)和生命線,數(shù)鵬通DQA數(shù)據(jù)質(zhì)量監(jiān)控平臺依據(jù)嚴謹?shù)臉I(yè)務(wù)規(guī)則實時監(jiān)控及跟蹤各種要素測量數(shù)據(jù)的準確性以及數(shù)據(jù)質(zhì)量情況,實時監(jiān)控各種要素數(shù)據(jù)變化。
Data quality is the base line of various method development, LinkCM DQA (Data Quality Assurance) platform following the rigorous methodology to ensure the data recorded frflect the actual facts, responses, observations and events.
基于影響的預(yù)測預(yù)報預(yù)警,通過多部門數(shù)據(jù)融合和數(shù)據(jù)再加工,將基礎(chǔ)數(shù)據(jù)轉(zhuǎn)換為信息,在信息中總結(jié)出知識,在知識中凝練出智慧,使大數(shù)據(jù)真正造福于人類文明。
Impact-based forecasting and alert, LinkCM is supporting on muti-business line data integration and further analysis, from data to information, from information to knowledge, from knowledge to wisdom.
數(shù)鵬通SYSBI統(tǒng)計分析及數(shù)據(jù)挖掘平臺,助力運營商實現(xiàn)實時位置數(shù)據(jù)采集、數(shù)據(jù)安全保護、聚合數(shù)據(jù)變現(xiàn)、用戶行為分析、個性化推薦。通過對大數(shù)據(jù)的挖掘、統(tǒng)計和分析,找到新的價值增長路線。
LinkCM SYSBI (Business Intelligence) platform, is supporting operators on real-time location information collection, privacy protection, data collaboration and realization, user behavior analysis, personalized recommendation. Through big data mining, statistic and analysis, find the new growth curve.
數(shù)鵬通(LinkCM)科技人工智能團隊是一個橫跨計算機科學(xué)、基礎(chǔ)數(shù)學(xué)、交互設(shè)計和心理學(xué)的多學(xué)科交叉融合團隊。我們旨在創(chuàng)造并開發(fā)下一代機器學(xué)習(xí)的技術(shù)并將其迅速落地為有價值的產(chǎn)品,目前已經(jīng)在客戶信用度等領(lǐng)域獲得了突破并成功的商業(yè)化運行。
LinkCM AI (Artificial Intelligence) team has experts from different domain, includes IT, Math, UI and psychology etc. We are aiming to create and develop next generation machine learning technology and apply is to valuable product, recently, the team already commercially lunched a consumer credit management solution.
智能計算領(lǐng)域涉及數(shù)據(jù)交換、人工智能和大數(shù)據(jù)應(yīng)用等技術(shù),是數(shù)字化時代的基礎(chǔ)支撐。從實時數(shù)據(jù)交換總線到自然語言識別,從數(shù)據(jù)質(zhì)量控制到智能預(yù)測研判,從統(tǒng)計分析數(shù)據(jù)挖掘到人工智能深度學(xué)習(xí)。數(shù)鵬通BDA,基于分布式架構(gòu)和人工智能的大數(shù)據(jù)體系,助力您的業(yè)務(wù)實現(xiàn)前所未有的價值。我們也強調(diào)基礎(chǔ)設(shè)施和系統(tǒng)架構(gòu)的可靠性與靈活性,案例經(jīng)驗分享如下: 安全可控原則 大力推進自主可控核心技術(shù)、關(guān)鍵軟硬件和技術(shù)裝備的規(guī)模應(yīng)用,不斷增強信息化基礎(chǔ)設(shè)施的韌性抗毀能力和安全保障能力,加強信息系統(tǒng)安全防護和大數(shù)據(jù)分級分類管理,確保系統(tǒng)和應(yīng)用可靠、可信、可控,滿足突發(fā)事件全天候、全方位、全過程應(yīng)急處置需要。 可維護性原則 用戶需求隨著時間的推移及社會的發(fā)展,有可能發(fā)生改變或新增,因此所選的結(jié)構(gòu)應(yīng)該是有良好的可維護性??刹捎媚K化設(shè)計和適當?shù)淖酉到y(tǒng)間的松耦合度,使得系統(tǒng)架構(gòu)可單獨對新的模塊或子系統(tǒng)進行維護而不需要對整體架構(gòu)進行大的調(diào)整。 可集成性原則 系統(tǒng)整體開發(fā)采用微服務(wù)架構(gòu)的技術(shù)路線,解決通用功能在不同場景下重復(fù)開發(fā)的問題,實現(xiàn)一個服務(wù)多地域、多應(yīng)用、多用戶的調(diào)用。 遵照開放系統(tǒng)的標準,確保軟硬件平臺的可移植性。 各體系和模塊的部署應(yīng)相對獨立,避免出現(xiàn)由于模塊功能的相互依賴性而不能啟動服務(wù)的情況等。 智能計算領(lǐng)域依托分布式架構(gòu)和微服務(wù)設(shè)計,通過彈性擴展與高可用部署,為復(fù)雜業(yè)務(wù)場景提供靈活高效的計算支持。結(jié)合大數(shù)據(jù)與AI技術(shù),構(gòu)建了數(shù)據(jù)驅(qū)動的智能決策系統(tǒng),實現(xiàn)實時精準的業(yè)務(wù)響應(yīng),為關(guān)鍵應(yīng)用提供可靠技術(shù)支撐。