Linked Data-Based Concept Recommendation: Comparison of Different Methods in Open Innovation Scenario

Abstract

Abstract. Concept recommendation is a widely used technique aimed to assist users to chose the right tags, improve their Web search experience and a multitude of other tasks. In finding potential problem solvers in Open Innovation (OI) scenarios, the concept recommendation is of a crucial importance as it can help to discover the right topics, directly or laterally related to an innovation problem. Such topics then could be used to identify relevant experts. We propose two Linked Data-based concept recommendation methods for topic discovery. The first one, hyProximity, exploits only the particularities of Linked Data structures, while the other one applies a well-known Information Retrieval method, Random Indexing, to the linked data. We compare the two methods against the baseline in the gold standard-based and user study-based evaluations, using the real problems and solutions from an OI company.

Combining a Co-occurrence-Based and a Semantic Measure for Entity Linking

“…The problem of discovering relationships between entities was also addressed by Damljanovic et al [6] in Open Innovation scenarios, where companies outsource tasks on a network of collaborators. Their approach exploits the links between entities extracted from both the user profiles and the task descriptions in order to match experts and tasks.…”

“…Furthermore, knowledge extraction and Named Entity Recognition (NER) tools and environments such as GATE [5], DBpedia Spotlight 4 , Alchemy 5 , AIDA 6 or Apache Stanbol 7 are increasingly applied to automatically generate structured data (entities) from unstructured resources such as Web sites, documents or social media. For example, such automatically generated data may provide some initial classification and structure, such as the association of terms with entity types defined in a structured RDF schema (as in [22]).…”

Linked Data-based Conceptual Modelling for Recommendation: A FCA-Based Approach

“…However, given a recommendation scenario (user set, items set and the interactions between them), the way in which this data can be linked with the items and users has to be defined. In this sense, some interesting approaches had been looked into, not only in the recommendation context [15,16,17]. Basically, these proposals follow two methods: the use of the SPARQL language to search for specific information (i.e.…”

Towards a Well-Interlinked Web Through Matching and Interlinking Approaches

“…Similar to Damljanovic et al [72], we distinguish between hierarchical and transversal relations in a given graph. Typical hierarchical properties in RDF graphs are, for instance, rdfs:…”

“…The problem of discovering relationships between entities was also addressed by Damljanovic et al [72] in Open Innovation scenarios, where companies outsource tasks on a network of collaborators. Their approach exploits the links between entities extracted from both the user profiles and the task descriptions in order to match experts and tasks.…”