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Results 1 - 10
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998
Reconsidering research on learning from media.
- Review of Educational Research,
, 1983
"... ABSTRACT. Recent meta-analyses and other studies of media influence on learning are reviewed. Consistent evidence is found for the generalization that there are no learning benefits to be gained from employing any specific medium to deliver instruction. Research showing performance or time-saving g ..."
Abstract
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Cited by 462 (6 self)
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. Studies of the influence of media on learning have been a fixed feature of educational research since However, this article will argue that most current summaries and meta-analyses of media comparison studies clearly suggest that media do not influence learning under my conditions. Even in the few cases
Matching words and pictures
- JOURNAL OF MACHINE LEARNING RESEARCH
, 2003
"... We present a new approach for modeling multi-modal data sets, focusing on the specific case of segmented images with associated text. Learning the joint distribution of image regions and words has many applications. We consider in detail predicting words associated with whole images (auto-annotation ..."
Abstract
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Cited by 665 (40 self)
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We present a new approach for modeling multi-modal data sets, focusing on the specific case of segmented images with associated text. Learning the joint distribution of image regions and words has many applications. We consider in detail predicting words associated with whole images (auto
Singling out Legal Knowledge from World Knowledge. An NLP–based approach
"... Abstract. Ontology learning in the legal domain rises the well-known problem of epistemological promiscuity between legal entities and regulated domain instances. In this paper, we propose a new term extraction approach specifically aimed at tackling such a problem through the acquisition of a term ..."
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Abstract. Ontology learning in the legal domain rises the well-known problem of epistemological promiscuity between legal entities and regulated domain instances. In this paper, we propose a new term extraction approach specifically aimed at tackling such a problem through the acquisition of a term
NLP-Based Requirements Modeling: Experiments on the Quality of the models ∗
- DEPARTMENTAL TECHNICAL REPORT
, 2004
"... Conceptual models are used in a variety of areas within Computer Science, including Software Engineering, Databases and AI. A major bottleneck in broadening their applicability is the time it takes to build a conceptual model for a new application. Not surprisingly, a variety of tools and techniques ..."
Abstract
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Cited by 1 (0 self)
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system. The tool used for the experiment – named NL-OOPS – extracts classes and associations from a knowledge base realized by a deep semantic analysis of a sample text. Specifically, NL-OOPS produces class models at different levels of detail by exploiting class hierarchies in the knowledge base of a
A Scalable Comparison-Shopping Agent for the World-Wide Web
- In Proceedings of the First International Conference on Autonomous Agents
, 1997
"... The Web is less agent-friendly than we might hope. Most information on the Web is presented in loosely structured natural language text with no agent-readable semantics. HTML annotations structure the display of Web pages, but provide virtually no insight into their content. Thus, the designers of i ..."
Abstract
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Cited by 327 (19 self)
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automatically extract information from unfamiliar Web sites? (4) What aspects of the Web facilitate this competence? In this paper we investigate these issues with a case study using the ShopBot. ShopBot is a fullyimplemented, domain-independent comparison-shopping agent. Given the home pages of several on
Acquiring Legal Ontologies from Domain-specific Texts
"... The paper reports on methodology and preliminary results of a case study in automatically extracting ontological knowledge from Italian legislative texts in the environmental domain. We use a fully-implemented ontology learning system (T2K) that includes a battery of tools for Natural Language Proce ..."
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The paper reports on methodology and preliminary results of a case study in automatically extracting ontological knowledge from Italian legislative texts in the environmental domain. We use a fully-implemented ontology learning system (T2K) that includes a battery of tools for Natural Language
Mining ontologies from text
- In Proceedings of the 12th European Workshop on Knowledge Acquisition, Modeling and Bahareh R. Heravi 199 Management (EKAW '00
, 2000
"... Abstract Ontologies have become an important means for structuring knowledge and building knowledge-intensive systems. For this purpose, eorts have been made to facilitate the ontology engineering process, in particular the acquisition of ontologies from domain texts. We present a general architectu ..."
Abstract
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Cited by 66 (5 self)
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architecture for discovering conceptual structures and engi-neering ontologies. Based on our generic architecture we describe a case study for mining ontologies from text using methods based on dictio-naries and natural language text. The case study has been carried out in the telecommunications domain
NLP Data Cleansing Based on Linguistic Ontology Constraints
"... Abstract. Linked Data comprises of an unprecedented volume of struc-tured data on the Web and is adopted from an increasing number of domains. However, the varying quality of published data forms a bar-rier for further adoption, especially for Linked Data consumers. In this paper, we extend a previo ..."
Abstract
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Cited by 2 (1 self)
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is – compared to other domains, such as biology – a late Linked Data adopter. However, it has seen a steep rise of activity in the creation of data and ontologies. NLP data quality assessment has become an important need for NLP datasets. In our study, we analysed 11 datasets using the lemon and NIF
Unsupervised ontological induction from text
- In Proc. of ACL
, 2010
"... Extracting knowledge from unstructured text is a long-standing goal of NLP. Although learning approaches to many of its subtasks have been developed (e.g., parsing, taxonomy induction, information extraction), all end-to-end solutions to date require heavy supervision and/or manual engineering, limi ..."
Abstract
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Cited by 43 (2 self)
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Extracting knowledge from unstructured text is a long-standing goal of NLP. Although learning approaches to many of its subtasks have been developed (e.g., parsing, taxonomy induction, information extraction), all end-to-end solutions to date require heavy supervision and/or manual engineering
Results 1 - 10
of
998
