WWW/Internet - Portal do Software Público Brasileiro

ISBN: 978-972-8939-25-0 © 2010 IADISIn this context, the main goal of this work is to improve a commonsense semantic network in order toperform better searches for analogies and to create meaningful analogies. We intend, through this strategy, tohelp teachers promoting meaningful learning.The paper is structured as follows: the first section shows an overview of the OMCS-Br Project that weadopt its commonsense semantic network that use Minsky’s model. The second one describes Gentner’stheory about analogy. The following section provides the experiments and our strategies to improve thesearch for analogies. The last section shows some conclusions of this work.1.1 OMCS-Br ProjectThe Open Mind Common Sense in Brazil (OMCS-Br) project, developed by the Advanced InteractionLaboratory (LIA) at Federal University of São Carlos (UFSCar) in collaboration with Media Lab fromMassachusetts Institute Technology (MIT), has been collected common sense of general public through aweb site which can be accessed by anyone through http://www.sensocomum.ufscar.br. The database isaccessible over the internet through an API for computer applications. This common sense database encodesthe relationships between statements generated by people though the common sense database project andrepresents cultural knowledge about specific subject. Of particular relevance to our project is that thedatabase provides demographics that allow us to access the beliefs, attitudes and vocabulary specific to aparticular age group in a particular geographic location.The website collects data from its visitors. After entering, a person can register and have access to variousactivities and themes available for them on this website in order to complete statements about the themes.Some examples of themes are Personal Preferences, Slang, Children Universe, Sexuality, Health and others.Statements are completed by filling in a template sentence pattern such as in Figure 1.Figure 1. Example of two templates where the dynamic part is filled in by the computer, the fixed part is the querystructure and the last part is where the user fills in their thoughtsWords or phrases are typed in by the users in natural language, parsed and stored. The parser derivestokens from the text and then interprets them using an engine that is based on Marvin Minsky´s model(Minsky, 1987) about knowledge representation. This engine generates a semantic network calledConceptNet (Liu and Singh, 2004), shown in Figure 2.The ConceptNet organizes the knowledge in a graph where nodes are the concepts and the directionallinks represent relations. In this paper, the relations based on Minsky’s model were defined as Minsky’srelation by us. For example, the template “banana is used for eat” (Figure 1) has a link labeled “UsedFor”between “banana” and “eat”. This template is stored as a tuple: {UsedFor “banana” “eat”}. There are othersrelations, such as: IsA, MotivationOf, DefinedAs, CapableOf, etc. as defined by Minsky (Liu and Singh,2004). His model has shown to be useful for culturally sensitive software development (Singh, 2002).Figure 2. Example of a semantic network36