Towards Constructive Text, Diagram, and Layout Generation for Information Presentation

Bateman, John A.; Kleinz, J.; Kamps, Thomas; Reichenberger, Klaus

doi:10.1162/089120101317066131

Cited by 67 publications

(49 citation statements)

References 17 publications

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“…Among these are the Document Structure Theory (Power et al, 2003), and the DArt bio system (Bateman et al, 2001). These approaches offer strong theoretical frameworks, but they were only implemented from a text generation point of view.…”

Section: Related Workmentioning

confidence: 99%

Proceedings of the Fourth Joint Conference on Lexical and Computational Semantics

2015

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will take place in Denver on June 4 and 5 and is colocated with SemEval and NAACL. As in 2014 at COLING, also on this occasion *SEM and SemEval chose to coordinate their programs by featuring a joint invited talk. In this way, *SEM aims to bring together the ACL SIGLEX and ACL SIGSEM communities.The acceptance rate of *SEM 2015 was quite competitive: out of 98 submissions, we accepted 36 papers for an overall acceptance of 37%. The acceptance rate of long paper that were accepted for oral presentation (18 out of 62) is 29%. The papers cover a wide range of topics including distributional semantics; lexical semantics and lexical acquisition; formal and linguistic semantics; discourse semantics; lexical resources, linked data and ontologies; semantics for applications; and extra-propositional semantics: sentiment and figurative meaning.The *SEM 2015 program consists of oral presentations for selected long papers and a poster session for long and short papers.Day One, June 4th:• Joint *SEM SemEval keynote talk by Marco Baroni;• Oral presentation sessions on distributional semantics, lexical semantics, and extra-propositional semantics;• Poster session.Day Two, June 5th:• Keynote talk by Preslav Natkov;• Oral presentation sessions on semantics for applications, lexical resources and ontologies, formal semantics, and discourse semantics;• *SEM Best Paper Award.We cannot finish without saying that *SEM 2015 would not have been possible without the considerable efforts of our area chairs, their reviewers, and the computational semantics community in general.We hope you will enjoy *SEM 2015, Distributional semantic methods have some a priori appeal as models of human meaning acquisition, because they induce word representations from contextual distributions naturally occurring in corpus data without need for supervision. However, learning the meaning of a (concrete) word also involves establishing a link between the word and its typical visual referents, which is beyond the scope of classic, text-based distributional semantics. Since recently several proposals have been put forward about how to induce multimodal word representations from linguistic and visual contexts, it is natural to ask if this line of work, besides its practical implications, can help us to develop more realistic, grounded models of human word learning within the distributional semantics framework.In my talk, I will report about two studies in which we used multimodal distributional semantics (MDS) to simulate human word learning. In one study, we first measured the ability of subjects to link a nonce word to relevant linguistic and visual associates when prompted only by exposure to minimal corpus evidence about it. We then simulated the same task with an MDS model, finding its behavior remarkably similar to that of subjects. In the second study, we constructed a corpus in which child-directed speech is aligned with real-life pictures of the objects mentioned by care-givers. We then trained our MDS model on these data, and inspected the generaliza...

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Section: Related Workmentioning

confidence: 99%

Proceedings of the Fourth Joint Conference on Lexical and Computational Semantics

2015

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“…Bateman et al [2] explore how to automatically construct the page layout (using rhetorical relationships and design heuristics) with the Dart bio prototype. VSAIH uses a presentation planner to select the best page layout (from a prefixed set of layouts), which can efficiently and flexibly combine different types of text descriptions and graphics.…”

Section: Related Workmentioning

confidence: 99%

Simulating Data Journalism to Communicate Hydrological Information from Sensor Networks

Molina

2012

Lecture Notes in Computer Science

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Abstract. Presenting relevant information via web-based user friendly interfaces makes the information more accessible to the general public. This is especially useful for sensor networks that monitor natural environments. Adequately communicating this type of information helps increase awareness about the limited availability of natural resources and promotes their better use with sustainable practices. In this paper, I suggest an approach to communicating this information to wide audiences based on simulating data journalism using artificial intelligence techniques. I analyze this approach by describing a pioneer knowledge-based system called VSAIH, which looks for news in hydrological data from a national sensor network in Spain and creates news stories that general users can understand. VSAIH integrates artificial intelligence techniques, including a model-based data analyzer and a presentation planner. In the paper, I also describe characteristics of the hydrological national sensor network and the technical solutions applied by VSAIH to simulate data journalism.

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“…Some recent research in NLG has explored the relationship between the rhetorical structure of an argument, and the document structure that expresses this argument in GENERATING MULTIMEDIA PRESENTATIONS FROM PLAIN TEXT TO SCREEN PLAY 9 a text (Bateman et al, 2001;Power et al, 2003a). At a rhetorical level, our example includes a procedure for taking the medicine; this procedure comprises a goal (taking a tablet) and a method, which consists in turn of a sequence of steps.…”

Section: Layout and Meaningmentioning

confidence: 99%

Generating Multimedia Presentations from Plain Text to Screen Play

Piwek

Power

Scott

et al. 2005

Multimodal Intelligent Information Presentation

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Abstract. In many Natural Language Generation (NLG) applications, the output is limited to plain texti.e., a string of words with punctuation and paragraph breaks, but no indications for layout, or pictures, or dialogue. In several projects, we have begun to explore NLG applications in which these extra media are brought into play. This paper gives an informal account of what we have learned. For coherence, we focus on the domain of patient information leaflets, and follow an example in which the same content is expressed first in plain text, then in formatted text, then in text with pictures, and finally in a dialogue script that can be performed by two animated agents. We show how the same meaning can be mapped to realisation patterns in different media, and how the expanded options for expressing meaning are related to the perceived style and tone of the presentation. Throughout, we stress that the extra media are not simple added to plain text, but integrated with it: thus the use of formatting, or pictures, or dialogue, may require radical rewording of the text itself.

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Towards Constructive Text, Diagram, and Layout Generation for Information Presentation

Cited by 67 publications

References 17 publications

Proceedings of the Fourth Joint Conference on Lexical and Computational Semantics

Proceedings of the Fourth Joint Conference on Lexical and Computational Semantics

Simulating Data Journalism to Communicate Hydrological Information from Sensor Networks

Generating Multimedia Presentations from Plain Text to Screen Play

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