This paper reports on theoretical investigations about the assumptions underlying the inverse document frequency (idf). We show that an intuitive idf-based probability function for the probability of a term being informative assumes disjoint document events. By assuming documents to be independent rather than disjoint, we arrive at a Poisson-based probability of being informative. The framework is useful for understanding and deciding the parameter estimation and combination in probabilistic retrieval models
Some researchers have recently argued that the task of Information Retrieval (IR) may successfully b...
I present three well-known probabilistic models of information retrieval in tutorial style: The bina...
Every information retrieval (IR) model embeds in its scoring function a form of term frequency (TF) ...
There have been a number of prior attempts to theoretically justify the effectiveness of the inverse...
This paper presents a new probabilistic model of information retrieval. The most important modeling ...
This paper presents the process of refining the document and their terms in Information Retrieval. I...
In document analysis, an important task is to automatically find keywords which best describe the su...
Retrieval models are the core components of information retrieval systems, which guide the document ...
Abstract. This paper presents a new probabilistic model of information retrieval. The most important...
We introduce and create a framework for deriving probabilistic models of Information Retrieval. The ...
This paper presents a new probabilistic model of information retrieval. The most important modeling ...
The 2-Poisson model for term frequencies is used to suggest ways of incorporating certain variables ...
Document fields, such as the title or the headings of a document, offer a way to consider the struct...
Probabilistic models require the notion of event space for defining a probability measure. An event ...
Based on the Shannon information theory, a measure for term value is introduced. This study is an a...
Some researchers have recently argued that the task of Information Retrieval (IR) may successfully b...
I present three well-known probabilistic models of information retrieval in tutorial style: The bina...
Every information retrieval (IR) model embeds in its scoring function a form of term frequency (TF) ...
There have been a number of prior attempts to theoretically justify the effectiveness of the inverse...
This paper presents a new probabilistic model of information retrieval. The most important modeling ...
This paper presents the process of refining the document and their terms in Information Retrieval. I...
In document analysis, an important task is to automatically find keywords which best describe the su...
Retrieval models are the core components of information retrieval systems, which guide the document ...
Abstract. This paper presents a new probabilistic model of information retrieval. The most important...
We introduce and create a framework for deriving probabilistic models of Information Retrieval. The ...
This paper presents a new probabilistic model of information retrieval. The most important modeling ...
The 2-Poisson model for term frequencies is used to suggest ways of incorporating certain variables ...
Document fields, such as the title or the headings of a document, offer a way to consider the struct...
Probabilistic models require the notion of event space for defining a probability measure. An event ...
Based on the Shannon information theory, a measure for term value is introduced. This study is an a...
Some researchers have recently argued that the task of Information Retrieval (IR) may successfully b...
I present three well-known probabilistic models of information retrieval in tutorial style: The bina...
Every information retrieval (IR) model embeds in its scoring function a form of term frequency (TF) ...