{'fraction_non_alphanumeric': 0.021404109589041095, 'fraction_numerical': 0.003424657534246575, 'mean_word_length': 5.152631578947369, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Dealing with P2P semantic heterogeneity through query expansion and interpretation

In P2P systems where query initiators and information providers do not necessarily share the same ontology, semantic interoperability generally relies on ontology matching or schema mappings. Information exchange is then not only enabled by the established correspondences (the "shared" parts of the ontologies) but, in some sense, limited to them. Then, to what extent the "unshared" parts can also contribute to and improve information exchange? In this paper, we address this question by considering a system where documents and queries are represented by semantic vectors. We propose a specific query expansion step at the query initiator's side and a query interpretation step at the document provider's. Through these steps, unshared concepts contribute to evaluate the relevance of documents wrt. a given query. Our experiments show that our method enables to correctly evaluate the relevance of a document even if concepts of a query are not shared. In some cases, we are able to find up to 90% of the documents that would be selected when all the central concepts are shared.