museumsandtheweb.com - steve.museum

Computational Linguistics in Museums: Applications for Cultural Datasets

schun — Sun, 27 Mar 2011 17:52:43 +0000

MW2011

Judith Klavans, University of Maryland; Robert Stein, Indianapolis Museum of Art; Susan Chun, Independent Consultant and Researcher; Raul David Guerra, University of Maryland, USA

Abstract

This paper presents work of the T3: Text, Tags, Trust project, an interdisciplinary collaboration of computational linguists, computer scientists, indexing and information retrieval experts, and museum professionals from the University of Maryland and Steve: The Museum Social Tagging Project. The authors define some key problems for managing large-scale datasets, share tools and resources developed for the project, and describe ways that these resources can be deployed by museums without expertise in language processing. In addition, the paper examines some of the ways in which analysis of data collected by the Steve project builds on our understanding of the ways in which users see and describe our collections. The specific challenges of applying batch-processing tools and methods to large, unstructured datasets are addressed, best practices for dealing with a number of sticky issues are shared, and promising applications for future research and promising application areas are considered.

Keywords: computational linguistics, social tagging, steve.museum, collection access, text processing, metadata

Program Item Reference:

Computational Linguistics in Museums: Applications for Cultural Datasets

rjstein — Fri, 24 Sep 2010 20:18:31 +0000

MW2011

Published Paper:

Computational Linguistics in Museums: Applications for Cultural Datasets

Keywords:

collection access

Keywords:

steve.museum

Keywords:

tagging

Keywords:

computational linguistics

Keywords:

text processing

Keywords:

cultural data

Abstract:

As museums continue to develop more sophisticated techniques for managing and analyzing cultural data, many are beginning to encounter challenges when trying to deal with the nuances of language and automated processing tools. How might user-generated comments be harvested and processed to determine the nature of the comment? Is it possible to use existing collection documentation to derive relations between similar objects? How can we train systems to automatically recognize (disambiguate) different meanings of the same word? Can automated language processing lead to more compelling browsing interfaces for online collections?

Luckily, a good deal of expertise and tools exist within the field of computational linguistics that can be applied to these problems to achieve meaningful results. Informed by previous work in computational linguistics and relevant project experience, the authors will address a number of these questions providing insight about how answers to impact museum practice might be found. Authors will share tools and resources that museum software developers can use to prototype and experiment with these techniques - without being experts in language processing themselves. In addition, the authors will describe the work of the T3: Text, Tags, Trust research project and how they have applied these tools to a large shared dataset of object metadata and social tags collected by the Steve.museum project.

Specific challenges regarding batch-processing tools and large datasets will be addressed. Best practices and algorithms will be shared for dealing with a number of sticky issues. Directions for future research and promising application areas will be also be discussed.

Type:

Paper - in formal session

Tagging

Authors:

Judith Klavans

Robert Stein

Susan Chun

Raul Guerra

Open Source Collaboration: New Models for Technology Development in the Museum Community

biblio — Wed, 14 Apr 2010 22:10:53 +0000

Wilde, E., & Mann L. (2010). Open Source Collaboration: New Models for Technology Development in the Museum Community. (Trant, Jennifer, David Bearman, Ed.).Museums and the Web.