Conceptual structures: information processing in mind and machine
Conceptual structures: information processing in mind and machine
Polynomial Algorithms for Projection and Matching
Proceedings of the 7th Annual Workshop on Conceptual Structures: Theory and Implementation
A content-search information retrieval process based on conceptual graphs
Knowledge and Information Systems
Conceptual Graphs and Ontologies for Information Retrieval
ICCS '07 Proceedings of the 15th international conference on Conceptual Structures: Knowledge Architectures for Smart Applications
Top-k Exploration of Query Candidates for Efficient Keyword Search on Graph-Shaped (RDF) Data
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
SPARK: adapting keyword query to semantic search
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
Q2Semantic: a lightweight keyword interface to semantic search
ESWC'08 Proceedings of the 5th European semantic web conference on The semantic web: research and applications
SemSearch: a search engine for the semantic web
EKAW'06 Proceedings of the 15th international conference on Managing Knowledge in a World of Networks
Expressing conceptual graph queries from patterns: how to take into account the relations
ICCS'11 Proceedings of the 19th international conference on Conceptual structures for discovering knowledge
A semantic web interface using patterns: the SWIP system
GKR'11 Proceedings of the Second international conference on Graph Structures for Knowledge Representation and Reasoning
Allowing end users to query graph-based knowledge bases
EKAW'12 Proceedings of the 18th international conference on Knowledge Engineering and Knowledge Management
Evaluating question answering over linked data
Web Semantics: Science, Services and Agents on the World Wide Web
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Our goal is to hide the complexity of formulating a query expressed in a graph query language such as conceptual graphs. We propose a mechanism for querying a collection of documents previously annotated by means of conceptual graphs. Our queries are based on keywords given by the user. Our system associates the keywords with their corresponding concepts. Then it selects a set of patterns which are pre-written typical queries. The patterns are instantiated according to the initial keywords. Finally, the user can modify the pre-written query he/she selects in order to fit his/her initial needs as well as possible. The query graph obtained is projected into the annotation graphs associated with the documents. The documents which answer the query are returned to the user.