Call for Papers: LVI 2013: Law via the Internet Conference

The call for papers and presentation proposals has been issued for LVI 2013: Law via the Internet Conference, to be held 26-27 September 2013 on the Channel Island of Jersey.

The conference Website does not seem to state the deadline for submitting papers or proposals. If you know the submission deadline, please feel free to tell us in the comments to this post.

[UPDATE 11 February 2013: The conference organizers now say the submission deadline is 31 March 2013.]

Papers are invited on the topics covered by any of the seven tracks in which the conference program is divided:

• E-Learning: distance, blended, open, mobile, gaming, MOOCing and more?
• Online legal information – starting from scratch
• Legal knowledge in the age of the semantic web
• Communicating our work: journals, blogs and other ways of publishing about open access
• Privacy v open government in legal publishing
• Emerging patterns of information access and usage
• Technological development and free access to law

The conference Twitter account is @JerseyLVI2013 and the conference hashtag is #lvi2013

For details about the tracks, please see the track Websites.

For more details about the conference, please see the conference Website.

Call for Papers: AICOL 2013: Workshop on AI Approaches to the Complexity of Legal Systems

A call for papers — with abstract submission deadline of 28 February 2013 and full paper submission deadline of 15 May 2013 — has been issued for AICOL 2013: Workshop on AI Approaches to the Complexity of Legal Systems, to be held at a date to be determined, between 21 and 27 July 2013, in Belo Horizonte, Brazil.

The workshop is being collocated with XXVI. World Congress of Philosophy of Law and Social Philosophy.

Papers for AICOL 2013 are invited on the following topics:

• Law and Science
• Knowledge Management
• Law and Cognitive Science
• Cognitive schemas
• Law and Complexity Theory
• Law and Robotics
• Complex Systems
• Law and Mathematics
• Legal Theory
• Legal Graphic Representation
• Legal Culture
• Game Theory
• Computer Ethics
• Formalization of Legal Systems and Norms
• Artificial Societies
• Rules and Standards
• Argumentative Frameworks
• Agreement technologies
• Legal Ontologies
• Electronic Institutions
• Governance
• Legal Concepts
• Legal Information Retrieval
• Legal Thesauri
• Online Dispute Resolution
• Taxonomies
• Trends in e-Discovery, e-Courts, e-Administration
• Natural Language Processing (NLP)
• Legal Knowledge Acquisition
• Users’ studies
• Legal Knowledge Representation

For more details, please see the call.

HT Professor Dr. Monica Palmirani

Grimmer and Stewart on Text as Data: Automatic Content Analysis Methods for Legislative Texts

Professor Dr. Justin Grimmer of Stanford University and Brandon M. Stewart of Harvard University have published Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts, forthcoming in Political Analysis.

Here is the abstract:

Politics and political conflict often occur in the written and spoken word. Scholars have long recognized this, but the massive costs of analyzing even moderately sized collections of texts have hindered their use in political science research. Here lies the promise of automated text analysis: it substantially reduces the costs of analyzing large collections of text. We provide a guide to this exciting new area of research and show how, in many instances, the methods have already obtained part of their promise. But there are pitfalls to using automated methods—they are no substitute for careful thought and close reading and require extensive and problem-specific validation. We survey a wide range of new methods, provide guidance on how to validate the output of the models, and clarify misconceptions and errors in the literature. To conclude, we argue that for automated text methods to become a standard tool for political scientists, methodologists must contribute new methods and new methods of validation.

The paper includes discussion of automated content analysis of legislative texts.

HT @treycausey

Oldfather et al. on Automated Content Analysis, Court Opinions, and Legal Scholarly Methodology

Professor Chad M. Oldfather of Marquette University School of Law, Professor Dr. Joseph P. Bockhorst of the University of Wisconsin Madison Department of Electrical Engineering and Computer Science, and Brian P. Dimmer, Esq., have published Triangulating Judicial Responsiveness: Automated Content Analysis, Judicial Opinions, and the Methodology of Legal Scholarship, Florida Law Review, 64, 1189-1242 (2012).

Here is the abstract:

The increasing availability of digital versions of court documents, coupled with increases in the power and sophistication of computational methods of textual analysis, promises to enable both the creation of new avenues of scholarly inquiry and the refinement of old ones. This Article advances that project in three respects. First, it examines the potential for automated content analysis to mitigate one of the methodological problems that afflicts both content analysis and traditional legal scholarship — their acceptance on faith of the proposition that judicial opinions accurately report information about the cases they resolve and courts’ decisional processes. Because automated methods can quickly process large amounts of text, they allow for assessment of the correspondence between opinions and other documents in the case, thereby providing a window into how closely opinions track the information provided by the litigants. Second, it explores one such novel measure — the responsiveness of opinions to briefs — in terms of its connection to both adjudicative theory and existing scholarship on the behavior of courts and judges. Finally, it reports our efforts to test the viability of automated methods for assessing responsiveness on a sample of briefs and opinions from the United States Court of Appeals for the First Circuit. Though we are focused primarily on validating our methodology, rather than on the results it generates, our initial investigation confirms that even basic approaches to automated content analysis provide useful information about responsiveness, and generates intriguing results that suggest avenues for further study.

Lesmo, Mazzei, Palmirani, and Radicioni on an NLP System for Extracting Legal Modificatory Provisions

Professor Dr. Monica Palmirani of Università di Bologna Dipartimento di Scienze Giuridiche «Antonio Cicu» and CIRSFID, and Professor Dr. Leonardo Lesmo, Dr. Alessandro Mazzei, and Dr. Daniele P. Radicioni, all of Universita’ di Torino Dipartimento di Informatica, have published TULSI: an NLP system for extracting legal modificatory provisions, forthcoming in Artificial Intelligence and Law.

Here is the abstract:

In this work we present the TULSI system (so named after Turin University Legal Semantic Interpreter), a system to produce automatic annotations of normative documents through the extraction of modificatory provisions. TULSI relies on a deep syntactic analysis and a shallow semantic interpreter that are illustrated in detail. We report the results of an experimental evaluation of the system and discuss them, also suggesting future directions for further improvement.

Wyner on Problems and Prospects in the Automatic Semantic Analysis of Legal Texts

Dr. Adam Wyner of the University of Liverpool Department of Computer Science has published Problems and Prospects in the Automatic Semantic Analysis of Legal Texts, in LREC 2012 Conference Proceedings: Semantic Processing of Legal Texts (SPLeT-2012) Workshop, pp. 39-41.

Here is the abstract:

Legislation and regulations are expressed in natural language. Machine-readable forms of the texts may be represented as linked documents, semantically tagged text, or translation to a logic. The paper considers the latter form, which is key to testing consistency of laws, drawing inferences, and providing explanations relative to input. To translate laws to a machine-readable logic, sentences must be parsed and semantically translated. Manual translation is time and labour intensive, usually involving narrowly scoping the rules. While automated translation systems have made significant progress, problems remain. The paper outlines systems to automatically translate legislative clauses to a semantic representation, highlighting key problems and proposing some tasks to address them.

Quaresma on Legal Information Extraction ← Machine Learning Algorithms + Linguistic Information

Professor Dr. Paulo Quaresma of Universidade de Évora Departamento de Informática has published Legal Information Extraction ← Machine Learning Algorithms + Linguistic Information, in LREC 2012 Conference Proceedings: Semantic Processing of Legal Texts (SPLeT-2012) Workshop, pp. 37-38.

Here is the abstract:

In order to automatically extract information from legal texts we propose the use of a mixed approach, using linguistic information and machine learning techniques. In the proposed architecture, lexical, syntactical, and semantical information is used as input for specialized machine learning algorithms, such as support vector machines. This approach was applied to collections of legal documents and the preliminary results were quite promising.

Wyner and Peters on Semantic Annotations for Legal Text Processing using GATE Teamware

Dr. Adam Wyner of the University of Liverpool Department of Computer Science and Dr. Wim Peters of the University of Sheffield Department of Computer Science, have published Semantic Annotations for Legal Text Processing using GATE Teamware, in LREC 2012 Conference Proceedings: Semantic Processing of Legal Texts (SPLeT-2012) Workshop, pp. 34-36.

Here is the abstract:

Large corpora of legal texts are increasing available in the public domain. To make them amenable for automated text processing, various sorts of annotations must be added. We consider semantic annotations bearing on the content of the texts – legal rules, case factors, and case decision elements. Adding annotations and developing gold standard corpora (to verify rule-based or machine learning algorithms) is costly in terms of time, expertise, and cost. To make the processes efficient, we propose several instances of GATE’s Teamware to support annotation tasks for legal rules, case factors, and case decision elements. We engage annotation volunteers (law school students and legal professionals). The reports on the tasks are to be presented at the workshop.

For more information, please see Dr. Wyner’s post, Crowdsourced Legal Case Annotation.

Boella et al. on Using Legal Ontology to Improve Classification in the Eunomos Legal Document and Knowledge Management System

Professor Dr. Guido Boella of Università degli Studi di Torino Dipartimento di Informatica, and colleagues, have published Using Legal Ontology to Improve Classification in the Eunomos Legal Document and Knowledge Management System, in LREC 2012 Conference Proceedings: Semantic Processing of Legal Texts (SPLeT-2012) Workshop, pp. 13-20.

Here is the abstract:

We focus on the classification of descriptions of legal obligations in the Legal Taxonomy Syllabus. We compare the results of classification using increasing levels of semantic information. Firstly, we use the text of the concept description, analysed via the TULE syntactic parser, to disambiguate syntactically and select informative nouns. Secondly, we add as additional features for the classifier the concepts (via their ontological ID) which have been semi-automatically linked to the text by knowledge engineers in order to disambiguate the meaning of relevant phrases which are associated to concepts in the ontology. Thirdly, we consider concepts related to the prescriptions by relations such as deontological clause and sanction.

Venturi on the Design and Development of TEMIS: A Syntactically and Semantically Annotated Corpus of Italian Legislative Texts

Giulia Venturi of l’Istituto di Linguistica Computazionale del CNR di Pisa (ILC-CNR) has published Design and Development of TEMIS: a Syntactically and Semantically Annotated Corpus of Italian Legislative Texts, in LREC 2012 Conference Proceedings: Semantic Processing of Legal Texts (SPLeT-2012) Workshop, pp. 1-12.

Here is the abstract:

Methodological issues concerning the design and the development of TEMIS, a syntactically and semantically annotated corpus of Italian legislative texts, are presented and discussed in the paper. TEMIS is a heterogeneous collection of texts exemplifying different sub–varieties of Italian legal language, i.e. European, national and local texts. The whole corpus has been dependency annotated and a subset has been enriched with frame–based information by customizing the formalism of the FrameNet project. In both cases, a number of domain–specific extensions of the annotation criteria developed for the general language has been foreseen. The interest in building such a corpus stems from the increasing need for annotated collections of domain–specific texts recognized by both the Artificial Intelligence and Law (AI & Law) community and the Natural Language Processing (NLP) one. In two research communities the benefits of having a resource where both domain–specific content and its underlying linguistic structure are made explicit and aligned are widely acknowledged. To the author knowledge, this is the first annotated corpus of legal texts overtly devoted to be used for legal text processing applications based on NLP tools.