Connecting Archaeological Data and Grey Literature via Semantic Cross Search

Tudhope, Douglas; May, Keith; Binding, Ceri; Vlachidis, Andreas

doi:10.11141/ia.30.5

Cited by 29 publications

(46 citation statements)

References 9 publications

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“…The rules are developed and deployed within the NLP framework GATE (Cunningham and Scott 2004) and enable a cascading mechanism of matching conditions. OPTIMA contributed to the Semantic Technologies for Archaeological Research (STAR) project (Vlachidis et al 2010;Tudhope et al 2011), which explored the potential of semantic technologies in cross search and integration of archaeological digital resources. STAR and the follow-on STELLAR projects were collaborations between the Hypermedia Research Unit at the University of South Wales (then the University of Glamorgan) with English Heritage and the ADS, funded by the UK Arts and Humanities Research Council (AHRC).…”

Section: Optimamentioning

confidence: 99%

Archaeological Discriminant Applications of the Lubischew Test

Guerrero¹,

Serrano²,

Jiménez‐Arenas³

2015

Mathematics and Archaeology

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IntroductionArchaeologists generate large quantities of text, ranging from unpublished technical fieldwork reports (the 'grey literature') to synthetic journal articles. However, the indexing and analysis of these documents can be time consuming and lacks consistency when done by hand. It is also rarely integrated with the wider archaeological information domain, with bibliographic searches having to be undertaken independently of database queries, for example. Text mining offers a means of extracting information from large volumes of text, providing researchers with an easy way of locating relevant texts and also of identifying patterns in the literature. In recent years techniques of Natural Language Processing (NLP) and its subfield, Information Extraction (IE), have been adopted to allow researchers to find, compare and analyse relevant documents, and to link them to other types of data. This chapter introduces the underpinning mathematics and provides a short presentation of the algorithms and distance measures used, from the point of view of artificial intelligence and computational logic. It describes the different NLP schools of thought and compares the pros and cons of rule-based vs machine learning approaches to information extraction. The role of ontologies and named entity recognition will be discussed and the chapter demonstrates how IE can provide the basis for semantic annotation and how it contributes to the construction of a semantic web for archaeology. The authors have worked on a number of projects that have employed techniques from NLP and IE in Archaeology, including Archaeotools, STAR and STELLAR. The chapter describes the archaeological user needs requirement, drawing examples from several countries, and the authors present examples drawn from their own projects, and previous work by others, of how NLP and IE can contribute to addressing this need. The problems and challenges of employing text mining in the archaeological domain are discussed, as well as the potential benefits.

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Section: Optimamentioning

confidence: 99%

Archaeological Discriminant Applications of the Lubischew Test

Guerrero¹,

Serrano²,

Jiménez‐Arenas³

2015

Mathematics and Archaeology

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“…As with the biomedical domain, there is a desire to integrate both the published archaeological literature and grey literature with excavation datasets (Tudhope et al 2011), although since grey literature is not formally published its style can sometimes be less formal. While archaeological terminology has some specialised technical vocabulary, it is distinguished by use of common terms, some of which are employed in archaeologically specific ways, for example 'cut', 'context', 'deposit', 'find'.…”

Section: Semantic Annotation Of Archaeological Grey Literaturementioning

confidence: 99%

“…The project supports the efforts of English Heritage (EH) in trying to integrate the data from various archaeological projects and their associated activities and seeks to exploit the potential of semantic technologies and natural language processing techniques, for enabling semantically defined queries over archaeological digital resources (Tudhope et al 2011).…”

Section: Semantic Technologies For Archaeological Resources (Star) Prmentioning

confidence: 99%

“…In particular, the field of Cultural Heritage has benefited from projects such as Europeana, which delivers significant semantic enrichment to more than 6 million cross-Europe digital items (Gradmann 2010). The UK digital archaeology domain has been supported by projects such as Archaeotools (Jeffrey et.al 2009) and STAR -Semantic Technologies for Archaeological Resources (Tudhope et al 2011), which have provided semantic methods for linking archaeological resources.…”

Section: Introductionmentioning

confidence: 99%

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A pilot investigation of information extraction in the semantic annotation of archaeological reports

Vlachidis

Tudhope

2012

IJMSO

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Andreas Vlachidis is a Research Assistant in the HypermediaAbstract. The paper discusses a prototype investigation of semantic annotation, a form of metadata assigning conceptual entities to textual instances, in this case archaeological grey literature. The use of Information Extraction (IE), a Natural Language Processing (NLP) technique, is central to the annotation process while the use of Knowledge Organization System (KOS) is explored for the association of semantic annotation with both ontological and terminological references. The annotation process follows a rule-based information extraction approach using the GATE NLP toolkit, together with the CIDOC CRM ontology, its CRM-EH archaeological extension and English Heritage thesauri and glossaries. Results are reported from an initial evaluation, which suggest that these information extraction techniques can be applied to archaeological grey literature reports. Further work is discussed drawing on the evaluation and consideration of the characteristics of the archaeology domain.

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“…OPTIMA contributed to the Semantic Technologies for Archaeological Research (STAR) project [14], which explored the potential of semantic technologies in query and integration of archaeological digital resources. The output of the pipeline is delivered in the form of semantic indices, expressed as RDF triples that enable semantically defined information retrieval and cross-searching over disparate archaeological digital resources i.e.…”

Section: Introductionmentioning

confidence: 99%

The Semantics of Negation Detection in Archaeological Grey Literature

Vlachidis

Tudhope

2013

Communications in Computer and Information Science

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Abstract. Archaeological reports contain a great deal of information that conveys facts and findings in different ways. This kind of information is highly relevant to the research and analysis of archaeological evidence but at the same time can be a hindrance for the accurate indexing of documents with respect to positive assertions. The paper presents a method for adapting the biomedicine oriented negation algorithm NegEx to the context of archaeology and discusses the evaluation results of the new modified negation detection module. The performance of the module is compared against a "Gold Standard" and evaluation results are encouraging, delivering overall 89% Precision, 80% Recall and 83% F-Measure scores. The paper addresses limitations and future improvements of the current work and highlights the need for ontological modelling to accommodate negative assertions. It concludes that adaptation of the NegEx algorithm to the archaeology domain is feasible and that rule-based information extraction techniques are capable of identifying a large portion of negated phrases from archaeological grey literature.

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Connecting Archaeological Data and Grey Literature via Semantic Cross Search

Cited by 29 publications

References 9 publications

Archaeological Discriminant Applications of the Lubischew Test

Archaeological Discriminant Applications of the Lubischew Test

A pilot investigation of information extraction in the semantic annotation of archaeological reports

The Semantics of Negation Detection in Archaeological Grey Literature

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