Conjoint utilization of structured and unstructured information for planning interleaving deliberation in supply chains

Effective business planning requires seamless access and intelligent analysis of information in its totality to allow the business planner to gain enhanced critical business insights for decision support. Current business planning tools provide insights from structured business data (i.e. sales forecasts, customers and products data, inventory details) only and fail to take into account unstructured complementary information residing in contracts, reports, user\u27s comments, emails etc. In this article, a planning support system is designed and developed that empower business planners to develop and revise business plans utilizing both structured data and unstructured information conjointly. This planning system activity model comprises of two steps. Firstly, a business planner develops a candidate plan using planning template. Secondly, the candidate plan is put forward to collaborating partners for its revision interleaving deliberation. Planning interleaving deliberation activity in the proposed framework enables collaborating planners to challenge both a decision and the thinking that underpins the decision in the candidate plan. The planning system is modeled using situation calculus and is validated through a prototype development

Conjoint Mining of Data and Content with Applications in Business, Bio-medicine, Transport Logistics and Electrical Power Systems

Part 1: KeynoteInternational audienceDigital information within an enterprise consists of (1) structured data and (2) unstructured content. The structured data includes enterprise and business data like sales, customers, products, accounts, inventory and enterprise assets, etc. while the content includes contracts, reports, emails, customer opinions, transcribed calls, on-line inquires, complements and complaints. Further, cutting edge businesses also using GPS tracking or surveillance monitors as well as sensor technologies for productivity, performance and efficiency measures, and these are provided by outsourcers etc. Similarly in the Biomedical area, resources can be structured data say in Swiss- Prot or unstructured text information in journal articles stored in content repositories such as PubMed. The structured data and the unstructured content generally reside in entirely separate repositories with the former being managed by a DBMS and the latter by a content manager frequently provided by an outsourcer or vendor [76]. This separation is undesirable since the information content of these sources is complementary. Further, each outsourcer or vendor keep the data on their own Cloud, and data are not sharable between the vendor systems, and most vendor system were not integrated with the enterprise systems, and leaves the organization to consolidate the data and information manually for data analytics. Effective knowledge and information use requires seamless access and intelligent analysis of information in its totality to allow enterprises to gain enhanced critical insights. This is becoming even more important, as the proportion of structured to unstructured information has shifted from 50-50 in the 1960s to 5-95 today [1]. Unless we can effectively utilize the unstructured content conjointly with the structured data, we will only obtain very limited and shallow knowledge discovery from an increasingly narrow slice of information. The techniques developed in our research will then be used to address significant issues in three application areas, but potential applications with significant impact are much more extensive