Collecting and Processing Interaction Data for Recommendation Systems

摘要: Traditional recommendation systems in software engineering (RSSE) analyze artifacts stored large repositories to create relevant recommendations. More recently, researchers have started exploring interaction data as a new source of information—moving closer the creation and usage rather than just looking at outcome. In engineering, refers that captures describes interactions developers with using tools. For instance, might be edits or selections affect specific code entities webpages (artifacts) an integrated development environment web browser (tools). Interaction allows better investigate developers’ behaviors, their intentions, information needs, problems encountered, providing possibilities for precise While various use been proposed, there is variety being collected, way how processed used. this chapter, we survey summarize major approaches RSSEs recommendations based on data. Along this, propose conceptual framework collecting processing purpose recommendation.