In present world that mining large amounts of security data can help generate actionable intelligence and make the understanding of Internet attacks better. To deal with internet attacks what we really need is cyber situational and attack attribution. Cyber situational awareness is attracting much attention. Practical clustering algorithms require multiple data scans so we need a scalable multi...

Personalized medicine is the cornerstone of medical practice. It tailors treatments for specific conditions of an affected individual. The borders of personalized medicine are defined by limitations in technology and our understanding of biology, physiology and pathology of various conditions. Current advances in technology have provided physicians with the tools to investigate the molecular ma...

An increasing number of organizations are struggling to overcome “information paralysis” — there is so much data available that it is difficult to understand what is and is not relevant. In addition, managerial intuition and instinct are more prevalent than hard facts in driving organizational decisions. Organizational Data Mining (ODM) is defined as leveraging data mining tools and technologie...

To operate under a new value-based paradigm, oncology providers must develop the capability to aggregate, analyze, measure, and report their value proposition--that is, their outcomes and associated costs. How are oncology providers positioned currently to perform these functions in a manner that is actionable? What is the current state of analytic capabilities in oncology? Are oncology provide...

This paper describes a methodology for converting an influence net to an executable model, implemented using the Colored Petri Net formalism and tools, so that it can be used to assess the impact of a set of controllable events or actions on outcomes of interest; specifically the impact of various sequences and timing of those actionable events. With this methodology, alternative courses of act...

The data mining process consists of a series of steps ranging from data cleaning, data selection and transformation, to pattern evaluation and visualization. One of the central problems in data mining is to make the mined patterns or knowledge actionable. Here, the term actionable refers to the mined patterns suggest concrete and profitable actions to the decision-maker. That is, the user can d...

The itemsets discovered by traditional High Utility Itemsets Mining (HUIM) methods are more useful than frequent itemset mining outcomes; however, they are usually disordered and not actionable, and sometime accidental, because the utility is the only judgement and no relations among itemsets are considered. In this paper, we introduce the concept of combined mining to select combined itemsets ...

Emails in the workplace are often intentional calls to action for its recipients. We propose to annotate these emails for what action its recipient will take. We argue that our approach of action-based annotation is more scalable and theoryagnostic than traditional speech-act-based email intent annotation, while still carrying important semantic and pragmatic information. We show that our actio...

Disease predictive systems are intended to be management aids. With a few exceptions, these systems typically do not have direct sustained use by growers. Rather, their impact is mostly pedagogic and indirect, improving recommendations from farm advisers and shaping management concepts. The degree to which a system is consulted depends on the amount of perceived new, actionable information that...

This paper examines how norms develop and influence the planning of technological and organizational change. A case study highlights the influences of a broadly held management innovation as it is introduced into an existing organizational culture, demonstrating how norms play a role in attempts to introduce technical and management innovations. In the case, three sources of normative structuri...