Learning-based summarisation of XML documents

Amini, Massih R.; Tombros, Anastasios; Usunier, Nicolas; Lalmas, Mounia

doi:10.1007/s10791-006-9017-1

Cited by 11 publications

(4 citation statements)

References 29 publications

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“…Amini et al [2] aim at extracting the most important sentences of an XML document, using the structure of the text as additional features. Ramanath et al [16,17] propose methods for summarizing tree-structured XML documents within a constrained budget, focusing on data-centric XML such as IMDB or DBLP.…”

Section: Related Workmentioning

confidence: 99%

Entity Summarisation with Limited Edge Budget on Undirected and Directed Knowledge Graphs

2010

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Abstract. The paper concerns a novel problem of summarising entities with limited presentation budget on entity-relationship knowledge graphs and propose an efficient algorithm for solving this problem. The algorithm has been implemented in two variants: undirected and directed, together with a visualisation tool. Experimental user evaluation of the algorithm was conducted on real large semantic knowledge graphs extracted from the web. The reported results of experimental user evaluation are promising and encourage to continue the work on improving the algorithm.

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Section: Related Workmentioning

confidence: 99%

Entity Summarisation with Limited Edge Budget on Undirected and Directed Knowledge Graphs

2010

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“…The pervasive use of the XML format on the World Wide Web has motivated much research in the area of XML document retrieval, considering both content and structure of documents leading to structure-aware retrieval [13,14]. The nesting level in an XML tree is an example of a structural feature used to express the degree of relevance of a keyword [15,16]. While the efforts in the area of XML document retrieval do not deal with the unique characteristics of presentation slides, they motivate the incorporation of structural features, such as indentation depth, in slide retrieval.…”

Section: Overview Of Contributions and Related Workmentioning

confidence: 99%

Hierarchical Fuzzy Feature Similarity Combination for Presentation Slide Retrieval

Kushki

Ajmal

Plataniotis

2009

EURASIP J. Adv. Signal Process.

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This paper proposes a novel XML-based system for retrieval of presentation slides to address the growing data mining needs in presentation archives for educational and scholarly settings. In particular, contextual information, such as structural and formatting features, is extracted from the open format XML representation of presentation slides. In response to a textual user query, each extracted feature is used to compute a fuzzy relevance score for each slide in the database. The fuzzy scores from the various features are then combined through a hierarchical scheme to generate a single relevance score per slide. Various fusion operators and their properties are examined with respect to their effect on retrieval performance. Experimental results indicate a significant increase in retrieval performance measured in terms of precision-recall. The improvements are attributed to both the incorporation of the contextual features and the hierarchical feature combination scheme.

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“…However, the use of XML markup in text documents to improve summarization quality has been previously studied [1]. These recent techniques still deal with document-oriented XML -text documents augmented with XML markup -and not data-oriented XML where markup is used as additional input to the document summarization process.…”

Section: Related Workmentioning

confidence: 99%

Xoom

Ramanath

Kumar

2009

Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology

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Suppose there is a large corpus of XML documents, each of which describes a movie released in the last 30 years (for example, extracted from IMDB). A movie enthusiast wants to make a list of interesting movies based on various criteria, such as, the genre, lead actors, directors, etc. She first decides to narrow the focus to just thrillers. However, she then has to look into each document individually, since only then is it possible for her to tell whether the combination of actors, directors, etc. interests her. This would be timeconsuming if the documents in question contain hundreds of tags each. Instead, she could use our tool Xoom (XML-Zoom) which can extract and present the key information in every document. This would drastically cut down the time to go through the documents. She could then use Xoom to zoom into specific portions of each of the remaining documents, instead of opening and scanning them from top to bottom. In this proposal, we describe the construction of Xoom and outline a demonstration.

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Learning-based summarisation of XML documents

Cited by 11 publications

References 29 publications

Entity Summarisation with Limited Edge Budget on Undirected and Directed Knowledge Graphs

Entity Summarisation with Limited Edge Budget on Undirected and Directed Knowledge Graphs

Hierarchical Fuzzy Feature Similarity Combination for Presentation Slide Retrieval

Xoom

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