On 1/20/06, Klaus <[EMAIL PROTECTED]> wrote: > > Hi, > > >Actually, my problem is that, for instance, for a document d, Its feature > >vector may be keywords and concepts. > > What do you exactly mean by features vector? You are referring to the > predicate - object pairs, connected to one subject node, don't you?
The feature vector may be bigger than the object-predicate pairs. In my application, each document may be annotated with several concepts to say this document contains an instance of a class. Thus, each document will be indexed like (keywords in the document, concepts in the document) --> URI. >I don't know how to weight the two > >items. Right now, i used a stupid method, given a document d, i can > obtain > >a rank D based on keyword method. Also, it is annotated with a concept c > >(The most simple example) . People can have a rank C of these concepts > in > >the domain ontology, where the most relevant concepts should be the at > top > >of this concept list. Finally, document's rank is decided by the sum of > (C > >+D). > > I'm going to implement something like a pagerank algorithm for my search > engine. In Contrast to the google approach I cannot just count the edge, > of > one node, because of the know semantic I can weight them. Of course this > implies a knowledge of the domain ontology. For instance if there is a > predicate "cited_in_document" I could rank a document higher, if it is > often > cited. But I'm not sure about the results... I am very interesting at your approach. You can see the page rank like method used in the SWOOGLE. But the relations they used only some simple relations, Such as "import" (used in OWL files"). IF we can use the Semantic level relations, It's should be better. But I am not sure it can succeed, as it requires how to weight the relations. Klaus > > > --------------------------------------------------------------------- > To unsubscribe, e-mail: [EMAIL PROTECTED] > For additional commands, e-mail: [EMAIL PROTECTED] > > -- Regards Jiang Xing
