Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

Getting to YES. Negotiating Agreement Without Giving In

This paper summarizes the current state of the art and recent trends in software engineering economics. It provides an overview of economic analysis techniques and their applicability to software engineering and management. It surveys the field of software cost estimation, including the major estimation techniques available, the state of the art in algorithmic cost models, and the outstanding research issues in software cost estimation.

Software engineering economics

BACKGROUND-Software Process Improvement (SPI) is a systematic approach to increase the efficiency and effectiveness of a software development organization and to enhance software products. OBJECTIVE-This paper aims to identify and characterize evaluation strategies and measurements used to assess the impact of different SPI initiatives. METHOD-The systematic literature review includes 148 papers published between 1991 and 2008. The selected papers were classified according to SPI initiative, applied evaluation strategies, and measurement perspectives. Potential confounding factors interfering with the evaluation of the improvement effort were assessed. RESULTS-Seven distinct evaluation strategies were identified, wherein the most common one, “Pre-Post Comparison,” was applied in 49 percent of the inspected papers. Quality was the most measured attribute (62 percent), followed by Cost (41 percent), and Schedule (18 percent). Looking at measurement perspectives, “Project” represents the majority with 66 percent. CONCLUSION-The evaluation validity of SPI initiatives is challenged by the scarce consideration of potential confounding factors, particularly given that “Pre-Post Comparison” was identified as the most common evaluation strategy, and the inaccurate descriptions of the evaluation context. Measurements to assess the short and mid-term impact of SPI initiatives prevail, whereas long-term measurements in terms of customer satisfaction and return on investment tend to be less used.

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Evaluation and Measurement of Software Process Improvement—A Systematic Literature Review

A display apparatus includes an image processor which processes an image to display an image content; a display unit which displays thereon an image content that is processed by the image processor; and a controller which displays a user interface (UI) menu including a plurality of UI items to search the image content, as one of a two-dimensional (2D) layout by which the plurality of UI items are arranged in a 2D manner, and a three-dimensional (3D) layout by which the plurality of UI items are arranged in a 3D manner , and changes displaying the one of the layouts to display the other of the layouts according to a user's command while maintaining a continuity of the arrangement of the plurality of UI items. Accordingly, search for an image content can be efficiently performed by using a UI menu.

Display apparatus and control method thereof

The present invention comprises methods, system, and apparatuses for generating and delivering analytic results for any simple or highly complex problem for which data exists that software or similar automated means can analyze. The present invention thus contemplates methods, systems, apparatuses, software, software processes, computer-readable medium, and/or data structures to enable performance of these and other features. In one embodiment, a method of the present invention comprises extracting and converting data using a data management component into a form usable by a data mining component, performing data mining to develop a model in response to a question or problem posed by a user.

Platform independent plug-in methods and systems for data mining and analytics

It is common knowledge that to stay competitive, your software organization must continuously improve product quality and customer satisfaction, as well as lower software development costs and shorten delivery time. The paper considers how software tools are an effective way to improve software development variables such as productivity and product quality. It considers software tool selection and process improvement costs.

The impact of tools on software productivity

A system automatically generates a representative image to represent a video sequence of a video program, and facilitates editing and manipulating of the video program. The system comprises receiving means (such as a frame selector or a unit extractor) for receiving a frame having at least one unit from a sequence of frames, resolving means (such as a unit extractor) for resolving one of the at least one unit, and generating means (such as an image engine) for generating an image representative of the sequence based on the unit. The system may further comprise a sequence divider for dividing the video program into multiple video sequences, and a frame selector for selecting the first sequence from the multiple sequences. The system may also comprise a unit distinction engine for determining distinct units from the units resolved by the resolving means, a unit predominance engine for defining predominance of each of the distinct units, and a unit representation engine for determining the distinct units which most uniquely represent the first video sequence. The resolving means preferably generates the representative image based on the distinct units determined by the unit representation engine to represent the first video sequence most uniquely. The resolving means may include an enhancement module for adding artwork or other enhancements to the representative image.

System and method for automatically generating an image to represent a video sequence

Eliciting process models from software projects is a first significant step towards process improvement. In this paper, we present a method, called Elicit, for eliciting software process models from industrial software environments. What is significant about this method is that it has evolved from an intuitive state-the state that defines the immaturity of current elicitation methods-to a formally defined, repeatable, effective and quantified state. Over the last two years of its usage, the method has been used to elicit models from three industrial-scale processes: preliminary analysis, requirements engineering, and product planning and dependency management. The example given in the paper focuses on the requirements engineering process. >

Elicit: a method for eliciting process models

In one embodiment, a method includes accessing a first event profile that includes a seed event parameter and a first event parameter, calculating fraud scores for the first event parameter, accessing a second event profile that includes a second event parameter that corresponds to the first event parameter, calculating a fraud score for the second event parameter, and then identifying the second parameters as being associated with fraud. Fraud scores may be calculated based on the attributes of a parameter, the relation of the parameter to the seed parameter, and the fraud scores of any corresponding parameters.

Tilmann Bruckhaus

Papers

Platform independent plug-in methods and systems for data mining and analytics

The impact of tools on software productivity

System and method for automatically generating an image to represent a video sequence

Elicit: a method for eliciting process models

Identifying Fraudulent Users Based on Relational Information