A Principled Approach Using Fuzzy Set Theory for Passage-Based Document Retrieval

Dang, Edward Kai Fung; Luk, Robert W. P.; Allan, James

doi:10.1109/tfuzz.2020.2990110

Cited by 10 publications

(8 citation statements)

References 67 publications

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“…Retrieval experiments are performed on our own retrieval system (e.g., Dang et al, 2021) using a wide range of standard TREC test collections that span the history of TREC evaluation (Table 2). For diversity, collections of both newswire articles and webpages are used.…”

Section: Setup and Methodologymentioning

confidence: 99%

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A retrieval model family based on the probability ranking principle for ad hoc retrieval

Dang

Luk

Allan

2022

Asso for Info Science & Tech

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Many successful retrieval models are derived based on or conform to the probability ranking principle (PRP). We present a new derivation of a document ranking function given by the probability of relevance of a document, conforming to the PRP. Our formulation yields a family of retrieval models, called probabilistic binary relevance (PBR) models, with various instantiations obtained by different probability estimations. By extensive experiments on a range of TREC collections, improvement of the PBR models over some established baselines with statistical significance is observed, especially in the large Clueweb09 Cat-B collection.

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Section: Setup and Methodologymentioning

confidence: 99%

“…Conversely an irrelevant document means that all parts of it are not relevant to the query. The DRD principle conforms to the TREC evaluation policy 1 (Dang et al, 2021).…”

Section: Estimation Of the Probabilitiesmentioning

confidence: 99%

A retrieval model family based on the probability ranking principle for ad hoc retrieval

Dang

Luk

Allan

2022

Asso for Info Science & Tech

Self Cite

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“…A membership degree can generally be utilized to explain the fuzzy boundaries of objective items, according to fuzzy set theory [24]. e membership function can then be used to express the degree of membership.…”

Section: Build Relationship Fuzzy Matrixmentioning

confidence: 99%

Information Security Risk Management Model for Big Data

Yang

2022

Advances in Multimedia

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In the current society of rapid expansion of information, big data have achieved vigorous development in all walks of life, considerably promoting data transmission and information sharing. Meanwhile, individuals are becoming increasingly reliant on big data and the Internet, but at the same time, the threat of information security posed by big data is becoming increasingly visible. As a result, how to protect the information security of big data has piqued the interest of both government and businesses. The essence of information security management is risk management, which is closely related to each other. Therefore, this study focuses on the following two aspects of research work. On the one hand, most existing risk management models merely describe risk management in the abstract from a macro-level, and they lack research on risk assessment, making them ineffective. This research builds a novel information security risk management model on the basis of existing risk management models based on the concept of multidimensional risk management. To achieve multidimensional dynamic management of big data risks and to keep them within an acceptable range as much as possible, the model is divided into five levels and two dimensions. On the other hand, this research also optimizes and improves the fuzzy mathematical analysis method and proposes a fuzzy comprehensive assessment method as the core algorithm for the risk assessment layer in the model. As a post-event risk assessment method, the advantage of this method is that it can comprehensively consider factors affecting risk and can quantify some assessment factors in the real network to achieve an effective combination of qualitative and quantitative, thereby providing a basis for decision-making in risk analysis and risk control. Finally, the effectiveness of the risk model in the real application is verified by example analysis, and it is intended that the study work would provide assistance and assurance for big data information security management.

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“…The attributes of objects described by these concepts cannot be simply answered with “yes” or “no”. Therefore, the concept of fuzzy sets emerged in order to describe and deal with these fuzzy concepts 2 . By establishing appropriate membership functions and utilizing relevant operations and transformations of fuzzy sets, fuzzy objects can be analyzed.…”

Section: Introductionmentioning

confidence: 99%

A novel Hellinger distance-based regret theory method for spherical fuzzy decision making model and its application in logistics

Ren,

Zhou

2024

Sci Rep

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Actual decision making problems are often based on the company decision maker’s behavior factors, such as risk attitude, subjective preference, etc. Regret theory can well express the behavior of the decision maker. In this pursuit, a novel decision making method was developed, based on the regret theory for the multi-attribute decision making problem, in which attribute values were expressed by spherical fuzzy numbers. Distance measurement not only has extensive applications in fields such as pattern recognition and image processing, but also plays an important role in the research of fuzzy decision theory. The existing distance measures of spherical fuzzy set either have special cases of anti-intuition or are more complex in calculation, so finding suitable distance measures is also an important research topic in the decision-making theory of spherical fuzzy set. For this reason, we first establish a new distance of spherical fuzzy sets based on Hellinger distance of probability distribution. A decision maker’s perception utility value function is proposed using the new distance formula, which is used to measure the regretful and rejoice value. Then we establish an optimization model for solving the attribute weights, when the information of attribute weight was partially known. Subsequently, the comprehensive perceived utility values were utilized to rank the order of the alternatives. Finally, a numerical example of assessment of logistics providers is used to show that the new decision making method is effective and feasible.

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A Principled Approach Using Fuzzy Set Theory for Passage-Based Document Retrieval

Cited by 10 publications

References 67 publications

A retrieval model family based on the probability ranking principle for ad hoc retrieval

A retrieval model family based on the probability ranking principle for ad hoc retrieval

Information Security Risk Management Model for Big Data

A novel Hellinger distance-based regret theory method for spherical fuzzy decision making model and its application in logistics

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