Rivindu Perera

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Linked Open Data (LOD) is growing rapidly as a source of structured knowledge used in a variety of text processing applications. However, the applications using the LOD need to be able to mediate between the front end user interfaces and LOD. This often requires a natural language interpretation of this structured, linked data. We demonstrate a middle-tier(More)
Content selection is a highly domain dependent task responsible for retrieving relevant information from a knowledge source using a given communicative goal. This paper presents a domain independent content selection model using keywords as communicative goal. We employ DBpedia triple store as our knowledge source and triples are selected based on weights(More)
The concept of Linked Data has attracted increased interest in recent times due to its free and open availability and the sheer of volume. We present a framework to generate patterns which can be used to lexicalize Linked Data. We use DBpedia as the Linked Data resource which is one of the most comprehensive and fastest growing Linked Data resource(More)
Recent trends in Question Answering (QA) have led to numerous studies focusing on presenting answers in a form which closely resembles a human generated answer. These studies have used a range of techniques which use the structure of knowledge, generic linguistic structures and template based approaches to construct answers as close as possible to a human(More)