A New Relevance Feedback Algorithm Based on Vector Space Basis Change

Mbarek, Rabeb; Tmar, Mohamed; Hattab, Hawete

doi:10.1007/978-3-642-54903-8_30

Cited by 3 publications

(10 citation statements)

References 13 publications

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“…Finally, we compare our proposed model with all existing VSBC-based models. We show that our model has better performance over models of [8,20,15,16,18,17]…”

Section: Introductionmentioning

confidence: 85%

“…According to M elucci [20], a context is modeled by a vector space basis and its evolution is mod eled by a VSBC. M eluccideveloped a new contextbased model called IRiX: if B is a basis which describes a context, L (B ) is the event that a vector belongs to the subspace spanned by B and PB is a projector to this subspace, then the probability that a vector y is in the context described by B is [15,16] developed RF algorithms based on a VSBC. These RF algorithms improve the results of known models (BM25 model, Rocchio model).…”

Section: Vector Space Basis Changementioning

confidence: 99%

“…With respect to the initial vector space basis (index terms), relevant and irrelevant documents share some terms (at least the terms of the query which selected these documents). According to [15,16], the technique of VSBC is effective in separating relevant documents and irrelevant ones.…”

Section: Introductionmentioning

confidence: 99%

“…The best framework that could bring the VSBC technique into application is RF: the user shows relevant and irrelevant documents in an initial rank ing and instead of reformulating the query, we change the vector space basis in which it is written (as well as the documents). In [15,16] from the relevant ones. These approaches were evaluated on a RF framework and on a Pseudo Relevance Feedback (PRF) framework in [18].…”

Section: Introductionmentioning

confidence: 99%

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Vector Space Basis Change in Information Retrieval

Mbarek

Tmar

Hattab

2014

CyS

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The Vector Space Basis Change (VSBC) is an algebraic operator responsible for change of basis and it is parameterized by a transition matrix. If we change the vector space basis, then each vector com ponent changes depending on this matrix. The strategy of VSBC has been shown to be effective in separating relevant documents and irrelevant ones. Recently, using this strategy, some feedback algorithms have been de veloped. To build a transition matrix some optimization methods have been used. In this paper, we propose to use a simple, convenient and direct method to build a transition matrix. Based on this method we develop a relevance feedback algorithm. Experimental results on a TREC collection show that our proposed method is effective and generally superior to known VSBC-based models. We also show that our proposed method gives a statistically significant improvement over these models.

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“…Finally, we compare our proposed model with all existing VSBC-based models. We show that our model has better performance over models of [8,20,15,16,18,17]…”

Section: Introductionmentioning

confidence: 85%

Section: Vector Space Basis Changementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Vector Space Basis Change in Information Retrieval

Mbarek

Tmar

Hattab

2014

CyS

Self Cite

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“…The above proof of Proposition 3.3 involves Theorem A.3, which in turn involves a change of basis of a vector space. In [41][42][43][44][45] context is modeled by a basis of a vector space of the VSM. By Proposition 3.3, a certain type of invertible linear operators of a vector space of the VSM can be simplified to a type of diagonalizable linear operators by means of a change of context if context is modeled by a basis of a vector space of the VSM.…”

Section: Group Actions On a Vector Space Of The Vsmmentioning

confidence: 99%

Group-theoretical vector space model

Kim¹

2014

International Journal of Computer Mathematics

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This paper presents a group-theoretical vector space model (VSM) that extends the VSM with a group action on a vector space of the VSM. We use group and its representation theory to represent a dynamic transformation of information objects, in which each information object is represented by a vector in a vector space of the VSM. Several groups and their matrix representations are employed for representing different kinds of dynamic transformations of information objects used in the VSM. We provide concrete examples of how a dynamic transformation of information objects is performed and discuss algebraic properties involving certain dynamic transformations of information objects used in the VSM.

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Towards a Better Basis Search through a Surrogate Model-Based Epistasis Minimization for Pseudo-Boolean Optimization

2020

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Epistasis, which indicates the difficulty of a problem, can be used to evaluate the basis of the space in which the problem lies. However, calculating epistasis may be challenging as it requires all solutions to be searched. In this study, a method for constructing a surrogate model, based on deep neural networks, that estimates epistasis is proposed for basis evaluation. The proposed method is applied to the Variant-OneMax problem and the NK-landscape problem. The method is able to make successful estimations on a similar level to basis evaluation based on actual epistasis, while significantly reducing the computation time. In addition, when compared to the epistasis-based basis evaluation, the proposed method is found to be more efficient.

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A New Relevance Feedback Algorithm Based on Vector Space Basis Change

Cited by 3 publications

References 13 publications

Vector Space Basis Change in Information Retrieval

Vector Space Basis Change in Information Retrieval

Group-theoretical vector space model

Towards a Better Basis Search through a Surrogate Model-Based Epistasis Minimization for Pseudo-Boolean Optimization

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