OpenMinTED invites researchers, service providers and SMEs to submit proposals related to the development and integration of existing text mining/NLP applications or software components.

Marketing typically has the largest discretionary budget in any organization because of the variety of activities we do, but now it also has the largest discretionary technology budget. That shift of dollars away from IT has been causing tensions for some time, but marketers now must be at the head of the table when purchasing everything from CRM, to business intelligence and analytics tools, to ecommerce platforms, and of course the website. Just like technology, customer experience budget and planning will move more towards marketing--as will customer satisfaction KPIs. The entire customer journey from pre-sale to customer advocacy is part of the overall brand experience. "Predictive analytics driven by AI and machine learning are going to change the way we do just about everything" One of the biggest obstacles marketers still run into is resistance to change.

Archaeologists have uncovered the 250-year-old kitchen of Thomas Jefferson's enslaved chef, James Hemings, who introduced mac and cheese and meringues into US culture. Hemings became the property of Thomas Jefferson in January of 1774 when he was just nine years old. His younger sister is Sally Hemings, who had six children believed to have been fathered by Jefferson after the death of his wife Martha Jefferson. Archaeologists have uncovered the 250-year-old kitchen of Thomas Jefferson's enslaved chef, James Hemings, who introduced mac and cheese into US culture. Growing up, Hemings was one of Jefferson's favorite servants and even accompanied him to Paris, France, in 1784.

You might think that you have the best CRM product on the market and best overall customer engagement, at least the best-maintained CRM as it relates to quality of data, right? However, what if you could apply machine learning to that CRM copper mine and turn it into a gold mine? Essentially, you could predict outcomes and close times, discover opportunity insights, automate certain customer service tasks, possibly suggest next steps in the sales process. While the list could go on, these are just a few areas where machine learning could be leveraged to capture more opportunities and help prevent service recovery situations. We've already mentioned a few ways that machine learning can improve your sales predictions and improve customer engagement, but harnessing its true power you can do so much more.

In this paper we present a loss-based approach to change point analysis. In particular, we look at the problem from two perspectives. The first focuses on the definition of a prior when the number of change points is known a priori. The second contribution aims to estimate the number of change points by using a loss-based approach recently introduced in the literature. The latter considers change point estimation as a model selection exercise. We show the performance of the proposed approach on simulated data and real data sets.

Zeiss Zen Intellesis, a new machine learning capability that enables researchers to perform advanced analysis of their imaging samples across multiple microscopy methods has been luanched. The first algorithmic solution introduced by the platform makes integrated, easy to use, powerful segmentation for 2D and 3D datasets available to the routine microscopy user. The software is available for the company's full range of optical, confocal, X-ray, electron and ion microscopes.

Editor: Jerome Feldman's "Essay Concerning Robotic Understanding" (AI Magazine, Fall 1990) shows a remarkable naivete about humans. Although he admits to some limitations on human understanding (understanding/h): "We actually use understanding/h loosely, normally excluding infants, idiots and so on. We acknowledge that there are strong limitations on the extent to which we can convey understanding/h across barriers of gender, race and culture." If we are using understanding/h in Locke's sense, to mean reason, with all its eighteenth century freight, including the exclusion of women and blacks from the category of reasoning beings, there are, strangely enough, no barriers to this category for machines. After all, Boole later invented his logic to help mechanize the process of jurisprudence.

Moreover, the system was designed from the beginning to be maintained on an ongoing basis without the involvement of senior knowledge engineers. In the manufacture of paper, wood is first pulped to separate its fibers. One of the predominant pulp processes is done in a kraft pulp mill and consists of cooking wood chips at elevated temperature and pressure in the presence of certain chemicals (alkali and sulfide), washing the resultant brown pulp, bleaching to make the pulp white, and drying the pulp for shipment to a paper mill. Pitch, or wood resin, is the material in wood that is insoluble in water but soluble in organic solvents. It usually makes up 14 percent of the weight of wood after the bark is removed and is often a sticky material.

Soil characteristics are extremely important when determining yield potential. Fertilization and liming are commonly used to adapt soils to the nutritional requirements of the crops to be cultivated. Planting the crop that will best fit the soil characteristics is an interesting alternative to minimize the need for soil treatment, reducing costs and potential environmental damages. In addition, farmers usually look for investments that offer the greatest potential earnings with the least possible risks. Regarding the objectives to be considered, the crop-selection problem may be difficult to solve using traditional tools.

Implementation of the case-based reasoner in rules and objects using a commercial knowledge-based system shell is described. Although some refinements remain, the performance of the case-based reasoner has met its design goals. The chemical industry is heavily regulated. Every hazardous chemical product must have a set of shipping descriptions that conform to strict regulations issued by the Department of Transportation (DOT), the International Maritime Organization (IMO), and the International Air Transport Association (IATA). Shipping descriptions provide a concise characterization of the hazards a chemical can present during transportation (figure 1). Failing to comply with transport regulations can result in penalties ranging from delayed shipments to heavy fines or even incarceration of corporate officials. In addition, each chemical product has a material safety data sheet (MSDS) that conforms to Occupational Safety and Health (OSHA) and American National Standards Institute (ANSI) standards. Unlike shipping descriptions, MSDSs are lengthy documents of 8 to 10 pages that provide a detailed description of the health hazards a product can pose in the workplace (figure 2). They also contain information on procedures for storing, handling, and disposing of a chemical. Inadequately prepared MSDSs can lead to substantial product-liability lawsuits against the company if the product is involved in an industrial accident. The ultimate goal of these regulations is to ensure proper communication of health and safety information for the protection of the public. Air Products is committed to the initiative of the Chemical Manufacturers Association (CMA) known as Responsible Care. This initiative focuses on the safe manufacturing, distribution, use, recycling, and disposal of chemicals. Proper communication through accurate shipping descriptions and full disclosure of hazard information in the MSDS plays a key role in fulfilling obligations under Responsible Care. Maintaining shipping descriptions and MSDSs requires a major effort. Most corporate systems are intensely manual.