報(bào)告題目：First Order Probabilistic Semantics in High-Level Information Fusion
報(bào) 告 人：Paulo C. G. Costa, Associate Professor
講座時(shí)間：2017年7月12日 上午10:00
講座地點(diǎn)：電子信息學(xué)院119會(huì)議室
邀 請(qǐng) 人：張建東
承辦學(xué)院：電子信息學(xué)院
聯(lián) 系 人：張建東
聯(lián)系電話(huà)：13630219356
報(bào)告簡(jiǎn)介：
Research on the subject of information fusion has focused primarily on lower-level data alignment (e.g. multi-sensor data fusion, syntactic protocols, distributed simulation, etc), on semantic mapping solutions (e.g. Semantic Web approaches, specialized semantic mapping solutions, etc), or other topics that do not fully address the fundamentals of high-level knowledge integration. As information flow in many real world applications grows larger and more complex, it becomes clear that advances in connectivity and computation alone are insufficient to address the problem of merging knowledge from heterogeneous sources. The sheer volume of data creates informational and cognitive bottlenecks. Incompatible formats and semantic mismatches necessitate tedious and time-consuming manual processing at various points in the decision cycle. As a result, massive amounts of potentially relevant data remain unexploited, narrow processing stovepipes continue to provide stop-gap solutions, and decision makers’ cognitive resources are too often focused on low-level manual data integration rather than high-level reasoning about the situations to be addressed.
This knowledge gap has been recognized and in spite of recent advances in HLIF research there is still a lack of a theoretical framework to enable HLIF applications. In this presentation, I introduce First-Order Probabilistic Semantics as a candidate for filling this gap, as it addresses the various challenges in merging complex data while properly accounting for the inherent uncertainty that comes from such data. I will present the key concepts of the framework and provide an update on the current status of its development, while showcasing a few examples of how the framework is being applied in diverse application areas.
報(bào)告人簡(jiǎn)介：
Paulo Cesar G. Costa博士是巴西空軍資深飛行員，2008年退役，現(xiàn)任美國(guó)喬治梅森大學(xué)系統(tǒng)工程與運(yùn)籌系副教授，喬治梅森大學(xué)C4I中心國(guó)際合作副主任，無(wú)線(xiàn)電與雷達(dá)工程實(shí)驗(yàn)室聯(lián)合主任。他的研究興趣包括電子戰(zhàn)、決策支持系統(tǒng)、多傳感器數(shù)據(jù)融合，概率表示和推理等。Costa教授開(kāi)發(fā)了PR-OWL，是UnBBayes-MEBN的重要貢獻(xiàn)者，Costa教授目前是美國(guó)NSF，美國(guó)國(guó)家工程院等審查委員會(huì)成員，IEEE高級(jí)會(huì)員，當(dāng)選國(guó)際信息融合學(xué)會(huì)（2016-2018年任期）理事會(huì)成員，2015年國(guó)際信息融合大會(huì)主席，現(xiàn)任ISIF工作組副主席。
