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Mallet (software Project)
MALLET is a Java "Machine Learning for Language Toolkit". Description MALLET is an integrated collection of Java code useful for statistical natural language processing, document classification, cluster analysis, information extraction, topic modeling and other machine learning applications to text. History MALLET was developed primarily by Andrew McCallum, of the University of Massachusetts Amherst, with assistance from graduate students and faculty from both UMASS and the University of Pennsylvania The University of Pennsylvania (also known as Penn or UPenn) is a private research university in Philadelphia. It is the fourth-oldest institution of higher education in the United States and is ranked among the highest-regarded universitie .... See also External links Official website of the projectat the University of Massachusetts Amherst * ThTopic Modeling Toolis an independently developed GUI that outputs MALLET results in CSV and HTML files Free artificial ...
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Andrew McCallum
Andrew McCallum is a professor in the computer science department at University of Massachusetts Amherst. His primary specialties are in machine learning, natural language processing, information extraction, information integration, and social network analysis. Career McCallum graduated summa cum laude from Dartmouth College in 1989. He completed his Ph.D. at University of Rochester in 1995 under the supervision of Dana H. Ballard. He was then a postdoctoral fellow, working with Sebastian Thrun and Tom M. Mitchell at Carnegie Mellon University. From 1998 to 2000 he was a Research Scientist and Research Coordinator at Justsystem Pittsburgh Research Center. From 2000 to 2002 was Vice President of Research and Development at WhizBang Labs, and Director of its Pittsburgh office. Since 2002, he worked as a professor of computer science at the University of Massachusetts Amherst. In 2020, he also joined Google as a part-time research scientist. He was elected as a fellow of the As ...
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Topic Model
In statistics and natural language processing, a topic model is a type of statistical model for discovering the abstract "topics" that occur in a collection of documents. Topic modeling is a frequently used text-mining tool for discovery of hidden semantic structures in a text body. Intuitively, given that a document is about a particular topic, one would expect particular words to appear in the document more or less frequently: "dog" and "bone" will appear more often in documents about dogs, "cat" and "meow" will appear in documents about cats, and "the" and "is" will appear approximately equally in both. A document typically concerns multiple topics in different proportions; thus, in a document that is 10% about cats and 90% about dogs, there would probably be about 9 times more dog words than cat words. The "topics" produced by topic modeling techniques are clusters of similar words. A topic model captures this intuition in a mathematical framework, which allows examining a set o ...
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Free Software Programmed In Java (programming Language)
Free may refer to: Concept * Freedom, having the ability to do something, without having to obey anyone/anything * Freethought, a position that beliefs should be formed only on the basis of logic, reason, and empiricism * Emancipate, to procure political rights, as for a disenfranchised group * Free will, control exercised by rational agents over their actions and decisions * Free of charge, also known as gratis. See Gratis vs libre. Computing * Free (programming), a function that releases dynamically allocated memory for reuse * Free format, a file format which can be used without restrictions * Free software, software usable and distributable with few restrictions and no payment * Freeware, a broader class of software available at no cost Mathematics * Free object ** Free abelian group ** Free algebra ** Free group ** Free module ** Free semigroup * Free variable People * Free (surname) * Free (rapper) (born 1968), or Free Marie, American rapper and media personali ...
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Natural Language Processing Toolkits
Nature, in the broadest sense, is the physical world or universe. "Nature" can refer to the phenomena of the physical world, and also to life in general. The study of nature is a large, if not the only, part of science. Although humans are part of nature, human activity is often understood as a separate category from other natural phenomena. The word ''nature'' is borrowed from the Old French ''nature'' and is derived from the Latin word ''natura'', or "essential qualities, innate disposition", and in ancient times, literally meant "birth". In ancient philosophy, ''natura'' is mostly used as the Latin translation of the Greek word ''physis'' (φύσις), which originally related to the intrinsic characteristics of plants, animals, and other features of the world to develop of their own accord. The concept of nature as a whole, the physical universe, is one of several expansions of the original notion; it began with certain core applications of the word φύσις by pre-Socr ...
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Free Artificial Intelligence Applications
Free may refer to: Concept * Freedom, having the ability to do something, without having to obey anyone/anything * Freethought, a position that beliefs should be formed only on the basis of logic, reason, and empiricism * Emancipate, to procure political rights, as for a disenfranchised group * Free will, control exercised by rational agents over their actions and decisions * Free of charge, also known as gratis. See Gratis vs libre. Computing * Free (programming), a function that releases dynamically allocated memory for reuse * Free format, a file format which can be used without restrictions * Free software, software usable and distributable with few restrictions and no payment * Freeware, a broader class of software available at no cost Mathematics * Free object ** Free abelian group ** Free algebra ** Free group ** Free module ** Free semigroup * Free variable People * Free (surname) * Free (rapper) (born 1968), or Free Marie, American rapper and media pers ...
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University Of Pennsylvania
The University of Pennsylvania (also known as Penn or UPenn) is a private research university in Philadelphia. It is the fourth-oldest institution of higher education in the United States and is ranked among the highest-regarded universities by numerous organizations and scholars. While the university dates its founding to 1740, it was created by Benjamin Franklin and other Philadelphia citizens in 1749. It is a member of the Ivy League. The university has four undergraduate schools as well as twelve graduate and professional schools. Schools enrolling undergraduates include the College of Arts and Sciences, the School of Engineering and Applied Science, the Wharton School, and the School of Nursing. Among its highly ranked graduate schools are its law school, whose first professor wrote the first draft of the United States Constitution, its medical school, the first in North America, and Wharton, the first collegiate business school. Penn's endowment is US$20.7 billio ...
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University Of Massachusetts Amherst
The University of Massachusetts Amherst (UMass Amherst, UMass) is a public research university in Amherst, Massachusetts and the sole public land-grant university in Commonwealth of Massachusetts. Founded in 1863 as an agricultural college, it is the flagship and the largest campus in the University of Massachusetts system, as well as the first established. It is also a member of the Five College Consortium, along with four other colleges in the Pioneer Valley: Amherst College, Smith College, Mount Holyoke College, and Hampshire College. As of Fall 2022, UMass Amherst has an annual enrollment of more than 32,000 students, along with approximately 1,900 faculty members. It is the largest university in Massachusetts by campus size and second largest university by enrollment in Massachusetts, after Boston University. The university offers academic degrees in 109 undergraduate, 77 master's and 48 doctoral programs. Programs are coordinated in nine schools and colleges. The Universit ...
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Machine Learning
Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, agriculture, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.Hu, J.; Niu, H.; Carrasco, J.; Lennox, B.; Arvin, F.,Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning IEEE Transactions on Vehicular Technology, 2020. A subset of machine learning is closely related to computational statistics, which focuses on making predicti ...
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Information Extraction
Information extraction (IE) is the task of automatically extracting structured information from unstructured and/or semi-structured machine-readable documents and other electronically represented sources. In most of the cases this activity concerns processing human language texts by means of natural language processing (NLP). Recent activities in multimedia document processing like automatic annotation and content extraction out of images/audio/video/documents could be seen as information extraction Due to the difficulty of the problem, current approaches to IE (as of 2010) focus on narrowly restricted domains. An example is the extraction from newswire reports of corporate mergers, such as denoted by the formal relation: :\mathrm(company_1, company_2, date), from an online news sentence such as: :''"Yesterday, New York based Foo Inc. announced their acquisition of Bar Corp."'' A broad goal of IE is to allow computation to be done on the previously unstructured data. A more sp ...
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Cross-platform
In computing, cross-platform software (also called multi-platform software, platform-agnostic software, or platform-independent software) is computer software that is designed to work in several computing platforms. Some cross-platform software requires a separate build for each platform, but some can be directly run on any platform without special preparation, being written in an interpreted language or compiled to portable bytecode for which the interpreters or run-time packages are common or standard components of all supported platforms. For example, a cross-platform application may run on Microsoft Windows, Linux, and macOS. Cross-platform software may run on many platforms, or as few as two. Some frameworks for cross-platform development are Codename One, Kivy, Qt, Flutter, NativeScript, Xamarin, Phonegap, Ionic, and React Native. Platforms ''Platform'' can refer to the type of processor (CPU) or other hardware on which an operating system (OS) or application runs, t ...
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Cluster Analysis
Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense) to each other than to those in other groups (clusters). It is a main task of exploratory data analysis, and a common technique for statistics, statistical data analysis, used in many fields, including pattern recognition, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning. Cluster analysis itself is not one specific algorithm, but the general task to be solved. It can be achieved by various algorithms that differ significantly in their understanding of what constitutes a cluster and how to efficiently find them. Popular notions of clusters include groups with small Distance function, distances between cluster members, dense areas of the data space, intervals or particular statistical distributions. Clustering can therefore be formulated as a multi-object ...
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Document Classification
Document classification or document categorization is a problem in library science, information science and computer science. The task is to assign a document to one or more classes or categories. This may be done "manually" (or "intellectually") or algorithmically. The intellectual classification of documents has mostly been the province of library science, while the algorithmic classification of documents is mainly in information science and computer science. The problems are overlapping, however, and there is therefore interdisciplinary research on document classification. The documents to be classified may be texts, images, music, etc. Each kind of document possesses its special classification problems. When not otherwise specified, text classification is implied. Documents may be classified according to their subjects or according to other attributes (such as document type, author, printing year etc.). In the rest of this article only subject classification is considered. T ...
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