Loading...
Please wait, while we are loading the content...
Similar Documents
PIRE: An extensible IR engine based on probabilistic
| Content Provider | CiteSeerX |
|---|---|
| Author | Nottelmann, Henrik |
| Abstract | Abstract. This paper introduces PIRE, a probabilistic IR engine. For both document indexing and retrieval, PIRE makes heavy use of probabilistic Datalog, a probabilistic extension of predicate Horn logics. Using such a logical framework together with probability theory allows for defining and using data types (e.g. text, names, numbers), different weighting schemes (e.g. normalised tf, tf.idf or BM25) and retrieval functions (e.g. uncertain inference, language models). Extending the system thus is reduced to adding new rules. Furthermore, this logical framework provide a powerful tool for including additional background knowledge into the retrieval process. 1 |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Extensible Ir Engine Logical Framework Retrieval Process Probabilistic Extension Language Model New Rule Probabilistic Ir Engine Probability Theory Probabilistic Datalog Heavy Use Document Indexing Retrieval Function Powerful Tool Predicate Horn Logic Data Type Uncertain Inference Normalised Tf Additional Background Knowledge |
| Content Type | Text |
| Resource Type | Article |
