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768
Meaningful Labeling of Integrated Query Interfaces
, 2006
"... The contents of Web databases are accessed through queries formulated on complex user interfaces. In many domains of interest (e.g. Auto) users are interested in obtaining information from alternative sources. Thus, they have to access many individual Web databases via query interfaces. We aim to co ..."
Abstract
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Cited by 12 (2 self)
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and grouping related attributes. In this paper, we investigate the naming of the attributes in the integrated query interface. We provide a set of properties which are required in order to have consistent labels for the attributes within an integrated interface so that users have no difficulty in understanding
ABSTRACT Meaningful Labeling of Integrated Query Interfaces
"... The contents of Web databases are accessed through queries formulated on complex user interfaces. In many domains of interest (e.g. Auto) users are interested in obtaining information from alternative sources. Thus, they have to access many individual Web databases via query interfaces. We aim to co ..."
Abstract
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and grouping related attributes. In this paper, we investigate the naming of the attributes in the integrated query interface. We provide a set of properties which are required in order to have consistent labels for the attributes within an integrated interface so that users have no difficulty in understanding
Labeling Images with a Computer Game
, 2004
"... We introduce a new interactive system: a game that is fun and can be used to create valuable output. When people play the game they help determine the contents of images by providing meaningful labels for them. If the game is played as much as popular online games, we estimate that most images on ..."
Abstract
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Cited by 773 (11 self)
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We introduce a new interactive system: a game that is fun and can be used to create valuable output. When people play the game they help determine the contents of images by providing meaningful labels for them. If the game is played as much as popular online games, we estimate that most images
Learning multiple layers of features from tiny images
, 2009
"... Groups at MIT and NYU have collected a dataset of millions of tiny colour images from the web. It is, in principle, an excellent dataset for unsupervised training of deep generative models, but previous researchers who have tried this have found it difficult to learn a good set of filters from the ..."
Abstract
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Cited by 280 (5 self)
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the images. We show how to train a multi-layer generative model that learns to extract meaningful features which resemble those found in the human visual cortex. Using a novel parallelization algorithm to distribute the work among multiple machines connected on a network, we show how training such a model
Meaningful Clusters
"... We present an approach to the disambiguation of cluster labels that capitalizes on the notion of semantic similarity to assign WordNet senses to cluster labels. The approach provides interesting insights on how document clustering can provide the basis for developing a novel approach to word sense d ..."
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We present an approach to the disambiguation of cluster labels that capitalizes on the notion of semantic similarity to assign WordNet senses to cluster labels. The approach provides interesting insights on how document clustering can provide the basis for developing a novel approach to word sense
Identifying meaningful locations
- Mobile and Ubiquitous Systems-Workshops, 2006. 3rd Annual International Conference on, IEEE, 2006
"... Abstract — Existing context-aware mobile applications often rely on location information. However, raw location data such as GPS coordinates or GSM cell identifiers are usually meaningless to the user and, as a consequence, researchers have proposed different methods for inferring so-called places f ..."
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Cited by 15 (4 self)
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from raw data. The places are locations that carry some meaning to user and to which the user can potentially attach some (meaningful) semantics. Examples of places include home, work and airport. A lack in existing work is that the labeling has been done in an ad hoc fashion and no motivation has been
Acoustically Meaningful Units
, 2009
"... The problem of keyword spotting in audio data has been explored for many years. Typically researchers use supervised methods to train statistical models to detect keyword instances. However, such supervised methods require large quantities of annotated data that is unlikely to be available for the m ..."
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for the majority of languages in the world. This thesis addresses this lack-of-annotation problem and presents two completely unsupervised spoken keyword spotting systems that do not require any transcribed data. In the first system, a Gaussian Mixture Model is trained to label speech frames with a Gaussian
Network Visualization by Meaningful Substrates
"... Networks have remained a challenge for information visualization designers because of the complex issues of node and link layout coupled with the rich set of tasks that users present. This paper offers a five-layer hierarchy of network visualization situations with associated tasks: from simple node ..."
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node and link situations to more elaborate situations involving node labels, directed links, node attributes, and link attributes. Then, it offers a strategy based on tying node placement to node attributes within nonoverlapping regions. These user-defined meaningful substrates enable users to easily
Unsupervised Discrimination and Labeling of Ambiguous Names
"... This paper describes adaptations of unsupervised word sense discrimination techniques to the problem of name discrimination. These methods cluster the contexts containing an ambiguous name, such that each cluster refers to a unique underlying person or place. We also present new techniques to assign ..."
Unsupervised Discrimination and Labeling of Ambiguous Names
"... This paper describes adaptations of unsupervised word sense discrimination techniques to the problem of name discrimination. These methods cluster the contexts containing an ambiguous name, such that each cluster refers to a unique underlying person or place. We also present new techniques to assign ..."
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