97 research outputs found
Conceptual Knowledge Processing with Formal Concept Analysis and Ontologies
No full textCimiano P, Stumme G, Hotho A, Tane J. Conceptual Knowledge Processing with Formal Concept Analysis and Ontologies. In: Eklund PW, ed. Concept Lattices, Second International Conference on Formal Concept Analysis, ICFCA 2004, Sydney, Australia, February 23-26, 2004, Proceedings. Lecture Notes in Computer Science, 2961. Springer; 2004: 189-207
Learning Concept Hierarchies from Text Corpora using Formal Concept Anaylsis
No full textCimiano P, Hotho A, Staab S. Learning Concept Hierarchies from Text Corpora using Formal Concept Anaylsis. Journal of Artificial Intelligence Research (JAIR). 2005;24:305-339
Learning Concept Hierarchies from Text Corpora using Formal Concept Analysis
No full textCimiano P, Hotho A, Staab S. Learning Concept Hierarchies from Text Corpora using Formal Concept Analysis. Karlsruhe: Universität Karlsruhe, Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB); 2004
Clustering Concept Hierarchies from Text
No full textCimiano P, Hotho A, Staab S. Clustering Concept Hierarchies from Text. In: Proceedings of the Conference on Lexical Resources and Evaluation (LREC). 2004: 1721-1724
Comparing Conceptual, Divise and Agglomerative Clustering for Learning Taxonomies from Text
No full textCimiano P, Hotho A, Staab S. Comparing Conceptual, Divise and Agglomerative Clustering for Learning Taxonomies from Text. In: López de Mántaras R, Saitta L, eds. Proceedings of the 16th European Conference on Artificial Intelligence, ECAI'2004, including Prestigious Applicants of Intelligent Systems, PAIS 2004. IOS Press; 2004: 435-439
Analyzing Tag Semantics Across Collaborative Tagging Systems
No full textThe objective of our group was to exploit state-of-the-art Information Retrieval methods for finding associations and dependencies between tags, capturing and representing differences in tagging behavior and vocabulary of various folksonomies, with the overall aim to better understand the semantics of tags and the tagging process. Therefore we analyze the semantic content of tags in the Flickr and Delicious folksonomies. We find that: tag context similarity leads to meaningful results in Flickr, despite its narrow folksonomy character; the comparison of tags across Flickr and Delicious shows little semantic overlap, being tags in Flickr associated more to visual aspects rather than technological as it seems to be in Delicious; there are regions in the tag-tag space, provided with the cosine similarity metric, that are characterized by high density; the order of tags inside a post has a semantic relevance
Nat.Lab. Unclassified Report 2002/840
No full textThis report describes the current state of the "ASC: speech coding" project that has as objective to develop a low bit rate (8-12 kbit/s), narrowband (8kHz sample frequency) sinusoidal audio and speech coder. The fundamental processing blocks of the implemented prototype are explained. Informal listening were conducted comparing a 14.5 kbit/s version of our coder with the 12.2 kbit/s GSM-EFR coder for both music and speech signals. Conclusions: A narrowband audio and speech coder has been developed that operates at a bit rate of 14.5 kbit/s. When comparing it to the 12.2 kbit/s GSM-EFR coder, it is found that our coder performs significantly better for music signals, while for speech it performs at most equally well. Because the bit rate achieved so far amounts to about 14.5 kbit/s, the low bit rate objective (8-12kbit/s) has not yet been reached. It is expected however, that improving the tracking of the coder may lead to the desired bit rate while the sound quality remains at least equal. Future work should also incorporate an amelioration of the sound quality for speech signals. Philips Electronics Nederland B.V. 2003 iv Contents 1
The CKC Challenge: Exploring Tools for Collaborative Knowledge Construction
No full textThe great success of Web 2.0 is mainly fuelled by an infrastructure that allows web users to create, share, tag, and connect content and knowledge easily. The tools for developing structured knowledge in this manner have started to appear as well. However, there are few, if any, user studies that are aimed at understanding what users expect from such tools, what works and what doesn't. We organized the Collaborative Knowledge Construction (CKC) Challenge to assess the state of the art for the tools that support collaborative processes for creation of various forms of structured knowledge. The goal of the Challenge was to get users to try out different tools and to learn what users expect from such tools /features that users need, features that they like or dislike. The Challenge task was to construct structured knowledge for a portal that would provide information about research. The Challenge design contained several incentives for users to participate. Forty-nine users registered for the Challenge; thirty three of them participated actively by using the tools. We collected extensive feedback from the users where they discussed their thoughts on all the tools that they tried. In this paper, we present the results of the Challenge, discuss the features that users expect from tools for collaborative knowledge constructions, the features on which Challenge participants disagreed, and the lessons that we learned
The Punya Platform: Building Mobile Research Apps with Linked Data and Semantic Features
No full textModern smartphones offer advanced sensing, connectivity, and processing capabilities for data acquisition, processing, and generation: but it can be difficult and costly to develop mobile research apps that leverage these features. Nevertheless, in life sciences and other scientific domains, there often exists a need to develop advanced mobile apps that go beyond simple questionnaires: ranging from sensor data collection and processing to self-management tools for chronic patients in healthcare. We present Punya, an open source, web-based platform based on MIT App Inventor that simplifies building Linked Data-enabled, advanced mobile apps that exploit smartphone capabilities. We posit that its integration with Linked Data facilitates the development of complex application and business rules, communication with heterogeneous online services, and interaction with the Internet of Things (IoT) data sources using the smartphone hardware. To that end, Punya includes an embedded semantic rule engine, integration with GraphQL and SPARQL to access remote graph data, and support for IoT devices using Bluetooth Low Energy and Linked Data Platform Constrained Application Protocol (LDP-CoAP). Moreover, Punya supports generating Linked Data descriptions of collected data. The platform includes built-in tutorials to quickly build apps using these different technologies. In this paper, we present a short discussion of the Punya platform, its current adoption that includes over 500 active users as well as the larger app-building MIT App Inventor community of which it is a part, and future development directions that would greatly benefit Semantic Web and Linked Data application developers as well as researchers who leverage Linked Open Data resources for their research. Resource: http://punya.mit.ed
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