Nettsider med emneord «semantic technologies»
In this thesis, you are expected to implement a method using the log of past queries for ranking and suggesting query extensions as a user formulates a query in OptiqueVQS -- a visual query formulation tool.
The master thesis will be carried out as a part of a recent EU project, called Optique (Scalable End-user Access to Big Data), and will give you opportunity to interact with top researchers all over the Europe.
Often information about the same entities (people, towns, songs, etc) is represented in different databases. These might be within one corporation or spread over the Web. In many cases, it is different to link this information, due to the lack of common identifiers across data sets.
In this thesis, you will investigate automated, heuristic methods for linking datasets, and infrastructure to extract information from a multitude of sources linked in this way.
In the LogID group at ifi, a “visual query formulation” tool has been developed, that allows constructing database queries by a combination of ontology navigation, faceted search, and graph manipulation. See the demo video below.
In this thesis, you will explore possibilities of enhancing the query construction possibilities by means of natural language processing technology. Users will be able to specify initial versions of queries using natural language. Queries can then be refined using e.g. a dialog system, or the existing query formulation tool.
The master thesis will be carried out as a part of a recent EU project, called Optique (Scalable End-user Access to Big Data), and will give you opportunity to interact with top researchers all over the Europe. It will also be co-supervised by ifi's LogID group and the Language Technology Group (LTG).
The challenge to be addressed is that many for many relationships between items in databases, there is a simple and a complicated story. For instance the simple story might be “Town A lies in country B.” The complicated story is “Town A lies in country B since 1990, according to the government of B, but only since 1995 according to the United Nations.” In a database containing the full information, queries will usually have to deal with the full details too.
The goal of this thesis is to extend and refine an existing visual user interface for query formulation in such a way that a) databases containing the full information can be queried, b) queries corresponding to the “simple story” can be constructed easily, without bothering users about the details, c) queries involving the details can be posed with a few clicks more.
The master thesis will be carried out as a part of a recent EU project, called Optique (Scalable End-user Access to Big Data), and will give you opportunity to interact with top researchers all over the Europe.
OptiqueVQS is a user interface to construct complex queries over data described by an ontology. The interface is very good for constructing complex queries that involve different types of entities, and filtering on their properties – but not so good at selecting types from a large class hierarchy.
We want to extend OptiqueVQS to allow navigating a class hierarchy while building a query.
In the LogID group at ifi, a “visual query formulation” tool has been developed, that allows constructing database queries by a combination of ontology navigation, faceted search, and graph manipulation. See the demo video below.
In this thesis, you will explore possibilities of enhancing the query construction possibilities by means of natural language processing technology. Users will be able to specify initial versions of queries using natural language. Queries can then be refined using e.g. a dialog system, or the existing query formulation tool.
The master thesis will be carried out as a part of a recent EU project, called Optique (Scalable End-user Access to Big Data), and will give you opportunity to interact with top researchers all over the Europe. It will also be co-supervised by ifi's LogID group and the Language Technology Group (LTG).
In this thesis, you will investigate how semantic technologies, together with recent trends in software engineering, can help solve information architecture challenges of complex enterprises. You will put your ideas to the test on selected case studies in DNB.
OptiqueVQS is a user interface to construct complex queries over data described by an ontology. One of the challenges when the ontology is large, is to present possible options to the user in such a way that the most "important" or "relevant" choices are at the top of the list of choices.
We approach this by comparing the query built so far to a log of previously built queries.
Selecting relevant options then becomes similar to recommending movies or books based on users’ known preferences. But we can additionally make use of the graph structure of queries, and the type hierarchy in the ontology.
OptiqueVQS is a user interface to construct complex queries over data described by an ontology. It is important for a good user experience to adjust the interface based on the available underlying data. But complex queries over large amounts of data are expensive.
We want to approach this problem by using search technology like Lucene/SOLR indices to build fast and scalable backend support for the query interface.
In this project, you will compare a recent ontology template language OTTR with well-established Semantic Web formalisms, namely query language SPARQL and constraint language SHACL.
The project has both a theoretical and a practical part; in the former, you will develop efficient algorithms for translation between the languages, while in the latter you will implement the algorithms and evaluate them on synthetic and real-life benchmarks. As a result, you will demonstrate that OTTR can be also used for querying ontologies and restricting their shape.