A Study on the Cognitive Plausibility of SIM-DL Similarity Rankings for Geographic Feature Types

نویسندگان

  • Krzysztof Janowicz
  • Carsten Keßler
  • Ilija Panov
  • Marc Wilkes
  • Martin Espeter
  • Mirco Schwarz
چکیده

The SIM-DL theory has been developed to enable similarity measurement between concept specifications using description logics. It thus closes the gap between similarity theories from psychology and formal representation languages from the AI community, such as the Web Ontology Language (OWL). In this paper, we present the results of a human participants test which investigates the cognitive plausibility of SIM-DL, that is, how well the rankings computed by the similarity theory match human similarity judgments. For this purpose, a questionnaire on the similarity between geographic feature types from the hydrographic domain was handed out to a group of participants. We discuss the set up and the results of this test, as well as the development of the according hydrographic feature type ontology and user interface. Finally, we give an outlook on the future development of SIM-DL and further potential application areas.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

COMPUTATIONAL AND COGNITIVE STUDIES IN SIMILARITY Evaluating a Neural Network Model of Visuospatial Similarity in Design

In this paper the cognitive plausibility of utilising selforganising maps in similarity assessments of 2D design diagrams is analysed using human-subject experiments which focus on designers. The experiments reported here are designed to address the validity of the computational approach to similarity and investigate feature types, feature salience and the role of context in cognitive assessments.

متن کامل

SIM-DLA: A Novel Semantic Similarity Measure for Description Logics Reducing Inter-concept to Inter-instance Similarity

While semantic similarity plays a crucial role for human categorization and reasoning, computational similarity measures have also been applied to fields such as semantics-based information retrieval or ontology engineering. Several measures have been developed to compare concepts specified in various description logics. In most cases, these measures are either structural or require a populated...

متن کامل

The Similarity Jury: Combining Expert Judgements on Geographic Concepts

A cognitively plausible measure of semantic similarity between geographic concepts is valuable across several areas, including geographic information retrieval, data mining, and ontology alignment. Semantic similarity measures are not intrinsically right or wrong, but obtain a certain degree of cognitive plausibility in the context of a given application. A similarity measure can therefore be s...

متن کامل

Identifying salient topics for personalized place similarity

The ability to find similar places is an important component to geographic information retrieval applications as varied as travel recommendation services, marketing analysis tools, and socio-ecological research. Using generative topic modelling on a large collection of place descriptions, we can represent places as distributions over thematic topics, and quantitatively measure similarity for pl...

متن کامل

Sim-DL: Towards a Semantic Similarity Measurement Theory for the Description Logic ALCNR in Geographic Information Retrieval

Similarity measurement theories play an increasing role in GIScience and especially in information retrieval and integration. Existing feature and geometric models have proven useful in detecting close but not identical concepts and entities. However, until now none of these theories are able to handle the expressivity of description logics for various reasons and therefore are not applicable t...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2008