Automatic Semantic Subject Indexing of Web Documents in Highly Inflected Languages

Sinkkilä, Reetta; Suominen, Osma; Hyvönen, Eero

doi:10.1007/978-3-642-21034-1_15

Cited by 6 publications

(6 citation statements)

References 17 publications

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“…If the amount of keywords for a document would have been 5 instead of 1 in the original annotations, the keyword would have been included in the list of generated keywords. The results are, however, similar but not fully comparable to the results of Sinkkilä et al [23] for different Finnish texts. AATOS performed well in contrast to the tools and strategies used in the study.…”

Section: Discussionsupporting

confidence: 48%

AATOS – A Configurable Tool for Automatic Annotation

Tamper

Leskinen

Ikkala

et al. 2017

Lecture Notes in Computer Science

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This paper presents an automatic annotation tool AATOS for providing documents with semantic annotations. The tool links entities found from the texts to ontologies defined by the user. The application is highly configurable and can be used with different natural language Finnish texts. The application was developed as a part of the WarSampo 1 and Semantic Finlex 2 projects and tested using Kansa Taisteli magazine articles and consolidated Finnish legislation of Semantic Finlex. The quality of the automatic annotation was evaluated by measuring precision and recall against existing manual annotations. The results showed that the quality of the input text, as well as the selection and configuration of the ontologies impacted the results.

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Section: Discussionsupporting

confidence: 48%

AATOS – A Configurable Tool for Automatic Annotation

Tamper

Leskinen

Ikkala

et al. 2017

Lecture Notes in Computer Science

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“…Typically the entities are organized in a knowledge base or ontology. The tools use different algorithms and training data, and few comparative evaluations have been conducted to identify the conditions under which each tool is the most appropriate [27,29,17]. However, due to the algorithms used, the tools work best on full-text documents but not on a user's search keywords.…”

Section: Semantic Annotationmentioning

confidence: 99%

Improving Access to Large-scale Digital Libraries ThroughSemantic-enhanced Search and Disambiguation

Hinze

Taube-Schock

Bainbridge

et al. 2015

Proceedings of the 15th ACM/IEEE-CS Joint Conference on Digital Libraries

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With 13,000,000 volumes comprising 4.5 billion pages of text, it is currently very difficult for scholars to locate relevant sets of documents that are useful in their research from the HathiTrust Digital Libary (HTDL) using traditional lexically-based retrieval techniques. Existing document search tools and document clustering approaches use purely lexical analysis, which cannot address the inherent ambiguity of natural language. A semantic search approach offers the potential to overcome the shortcoming of lexical search, but-even if an appropriate network of ontologies could be decided upon-it would require a full semantic markup of each document. In this paper, we present a conceptual design and report on the initial implementation of a new framework that affords the benefits of semantic search while minimizing the problems associated with applying existing semantic analysis at scale. Our approach avoids the need for complete semantic document markup using pre-existing ontologies by developing an automatically generated Concept-in-Context (CiC) network seeded by a priori analysis of Wikipedia texts and identification of semantic metadata. Our Capisco system analyzes documents by the semantics and context of their content. The disambiguation of search queries is done interactively, to fully utilize the domain knowledge of the scholar. Our method achieves a form of semantic-enhanced search that simultaneously exploits the proven scale benefits provided by lexical indexing.

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“…These allow you to process a lot of information quickly and cheaply, and also ensure the inter-indexer consistency. However automatic systems also present problems because of the complexity of natural language processing (Sinkkilä et al, 2011). Consequently the semi-automatic indexing approach is a good solution, because in addition to obviating the problems of the automatic indexing system it facilitates the the task of indexers by providing suitable term suggestions (Vasuki and Cohen, 2010).…”

Section: Research Objectivesmentioning

confidence: 99%

A semi-automatic indexing system based on embedded information in HTML documents

et al. 2015

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Purpose -This paper describes and evaluates the tool DigiDoc MetaEdit which allows the semi-automatic indexing of HTML documents. The tool works by identifying and suggesting keywords from a thesaurus according to the embedded information in HTML documents. This enables the parameterization of keyword assignment based on how frequently the terms appear in the document, the relevance of their position, and the combination of both.Design/methodology/approach -In order to evaluate the efficiency of the indexing tool, the descriptors/keywords suggested by the indexing tool are compared to the keywords which have been indexed manually by human experts. To make this comparison a corpus of HTML documents are randomly selected from a journal devoted to Library and Information Science.Findings -The results of the evaluation show that there: (1) is close to a 50% match or overlap between the two indexing systems, however if you take into consideration the related terms and the narrow terms the matches can reach 73%; and (2) the first terms identified by the tool are the most relevant.Originality/value -The tool presented identifies the most important keywords in an HTML document based on the embedded information in HTML documents. Nowadays, representing the contents of documents with keywords is an essential practice in areas such as information retrieval and e-commerce.

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Automatic Semantic Subject Indexing of Web Documents in Highly Inflected Languages

Cited by 6 publications

References 17 publications

AATOS – A Configurable Tool for Automatic Annotation

AATOS – A Configurable Tool for Automatic Annotation

Improving Access to Large-scale Digital Libraries ThroughSemantic-enhanced Search and Disambiguation

A semi-automatic indexing system based on embedded information in HTML documents

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