The Quantum Probability Ranking Principle (QPRP) has been recently proposed, and accounts for interdependent document relevance when ranking. However, to be instantiated, the QPRP requires a method to approximate the "interference" between two documents. In this poster, we empirically evaluate a number of different methods of approximation on two TREC test collections for subtopic retrieval. It is shown that these approximations can lead to significantly better retrieval performance over the state of the art
In the last years several works have investigated a formal model for Information Retrieval (IR) base...
We present a non-traditional retrieval problem we call subtopic re-trieval. The subtopic retrieval p...
A key concept in many Information Retrieval (IR) tasks, e.g. document indexing, query language model...
The Quantum Probability Ranking Principle (QPRP) has been recently proposed, and accounts for interd...
A known limitation of the Probability Ranking Principle (PRP) is that it does not cater for dependen...
In this work, we summarise the development of a ranking principle based on quantum probability theor...
While the Probability Ranking Principle for Information Retrieval provides the basis for formal mode...
While the Probability Ranking Principle for Information Retrieval provides the basis for formal mode...
In this thesis we investigate the use of quantum probability theory for ranking documents. Quantum p...
Abstract—Relevance Model (RM) is one of typical and generally stable methods for the query expansion...
Indexing is a core process of an information retrieval (IR) system (IRS). As indexing can neither be...
Quantum theory (QT) has recently been employed to advance the theory of information retrieval (IR). ...
Quantum theory has been applied in a number of fields outside physics, e.g., cognitive science and i...
We present a non-traditional retrieval problem we call subtopic retrieval. The subtopic retrieval pr...
In the last years several works have investigated a formal model for Information Retrieval (IR) base...
In the last years several works have investigated a formal model for Information Retrieval (IR) base...
We present a non-traditional retrieval problem we call subtopic re-trieval. The subtopic retrieval p...
A key concept in many Information Retrieval (IR) tasks, e.g. document indexing, query language model...
The Quantum Probability Ranking Principle (QPRP) has been recently proposed, and accounts for interd...
A known limitation of the Probability Ranking Principle (PRP) is that it does not cater for dependen...
In this work, we summarise the development of a ranking principle based on quantum probability theor...
While the Probability Ranking Principle for Information Retrieval provides the basis for formal mode...
While the Probability Ranking Principle for Information Retrieval provides the basis for formal mode...
In this thesis we investigate the use of quantum probability theory for ranking documents. Quantum p...
Abstract—Relevance Model (RM) is one of typical and generally stable methods for the query expansion...
Indexing is a core process of an information retrieval (IR) system (IRS). As indexing can neither be...
Quantum theory (QT) has recently been employed to advance the theory of information retrieval (IR). ...
Quantum theory has been applied in a number of fields outside physics, e.g., cognitive science and i...
We present a non-traditional retrieval problem we call subtopic retrieval. The subtopic retrieval pr...
In the last years several works have investigated a formal model for Information Retrieval (IR) base...
In the last years several works have investigated a formal model for Information Retrieval (IR) base...
We present a non-traditional retrieval problem we call subtopic re-trieval. The subtopic retrieval p...
A key concept in many Information Retrieval (IR) tasks, e.g. document indexing, query language model...