Deep learning based searching approach for RDF graphs
نویسندگان
چکیده
منابع مشابه
Random Indexing for Searching Large RDF Graphs
Querying large RDF spaces with traditional query languages such as SPARQL is challenging as it requires a familiarity with the structure of the RDF graph and the names (URIs) of its classes, properties and relevant individuals. In this paper, we propose a complementary approach based on Vector Space Models (VSM), more concretely Random Indexing (RI) [1] for building a semantic index for a large...
متن کاملSearching RDF Graphs with SPARQL and Keywords
The proliferation of knowledge-sharing communities like Wikipedia and the advances in automated information extraction from Web pages enable the construction of large knowledge bases with facts about entities and their relationships. The facts can be represented in the RDF data model, as so-called subject-property-object triples, and can thus be queried by structured query languages like SPARQL...
متن کاملDeep learning-based CAD systems for mammography: A review article
Breast cancer is one of the most common types of cancer in women. Screening mammography is a low‑dose X‑ray examination of breasts, which is conducted to detect breast cancer at early stages when the cancerous tumor is too small to be felt as a lump. Screening mammography is conducted for women with no symptoms of breast cancer, for early detection of cancer when the cancer is most treatable an...
متن کاملDeep Feature Learning for Graphs
This paper presents a general graph representation learning framework called DeepGL for learning deep node and edge representations from large (attributed) graphs. In particular, DeepGL begins by deriving a set of base features (e.g., graphlet features) and automatically learns a multi-layered hierarchical graph representation where each successive layer leverages the output from the previous l...
متن کاملA Query Approximating Approach Over RDF Graphs
Regardless of the knowledge structure lack about Resource Description Framework (RDF) data, difficulties, principally, occur in specifying and answering queries. Approximate querying is the solution to find relevant information by getting a set of sub structures (e.g. sub graphs) matching the query. Approaches based on the structure and others based on semantic, marginalized the common meaning ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: PLOS ONE
سال: 2020
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0230500