MsMLO:A novel approach for selecting and fusing learning objects

Retrieving Learning Objects (LO) that fulfills user's requirements, is still an issue. For instance, a user interested in linear regression topics (theoretical background) and examples (problems solved using a spreadsheet), might find two different resources covering these topics. Merging the two LOs as one would be a more appropriate solution rather than browsing them separately. This paper presents a novel approach for automatic selection of source LOs in order to construct a more appropriate one based on the users query. The combination of two or more LOs gathers not only knowledge but also tends to rank the new LO in a higher position than the source ones. This is accomplished by driving the merging process using the query. Our algorithm avoids including similar items in the new LO.