Deterministic solution of algebraic equations in sentiment analysis

Zahedi, Morteza; Basiri, Abdolali

doi:10.1007/s11042-023-15140-3

Cited by 3 publications

(1 citation statement)

References 82 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The purpose of the research in this article is to develop effective object recognition methods to solve the identification problem in the IoT ecosystem of the Aral region. The objective of the research is to develop correct recognition algorithms based on an algebraic approach in solving the problem of identifying [11][12][13][14][15] the flow of information in the IoT ecosystem of the Aral region, which is described in detail in work [15] of the authors of this paper.…”

Section: Introductionmentioning

confidence: 99%

Algebraic Recognition Approach in IoT Ecosystem

Kabulov,

Saymanov,

Babadjanov

et al. 2024

Mathematics

View full text Add to dashboard Cite

The solution to the problem of identifying objects in the IoT ecosystem of the Aral region is analyzed. The problem of constructing a correct algorithm with linear closure operators of a model for calculating estimates for identifying objects in the IoT ecosystem of the Aral region is considered. An algorithm operator is developed, which is considered correct for the problem Z, is the sum of q operators of the assessment calculation model, and is described by a set of numerical parameters 3·n·m·q, where n is the number of specified features, m is the number of reference objects, and q is the set of recognized objects. Within the framework of the algebraic approach, several variants of linear combinations of recognition operators are constructed, the use of which gives the correct answer on the control material, and this is proven in the form of theorems. The constructed correct recognition algorithms, which are the easiest to use, where there is no optimization procedure, make it possible to quickly solve the issue of identifying incoming information flows in the IoT ecosystem of the Aral region.

show abstract

Section: Introductionmentioning

confidence: 99%

Algebraic Recognition Approach in IoT Ecosystem

Kabulov,

Saymanov,

Babadjanov

et al. 2024

Mathematics

View full text Add to dashboard Cite

show abstract

A Hybrid Hierarchical Mathematical Heuristic Solution of Sparse Algebraic Equations in Sentiment Analysis

Jalali,

Zahedi,

Gharahbagh

et al. 2024

Information

View full text Add to dashboard Cite

Many text mining methods use statistical information as a text- and language-independent approach for sentiment analysis. However, text mining methods based on stochastic patterns and rules require many samples for training. On the other hand, deterministic and non-probabilistic methods are easier and faster to solve than other methods, but they are inefficient when dealing with Natural Language Processing (NLP) data. This research presents a novel hybrid solution based on two mathematical approaches combined with a heuristic approach to solve unbalanced pseudo-linear algebraic equation systems that can be used as a sentiment word scoring system. In its first step, the proposed solution uses two mathematical approaches to find two initial populations for a heuristic method. The heuristic solution solves a pseudo-linear NLP scoring scheme in a polarity detection method and determines the final scores. The proposed solution was validated using three scenarios on the SemEval-2013 competition, the ESWC dataset, and the Taboada dataset. The simulation results revealed that the proposed solution is comparable to the best state-of-the-art methods in polarity detection.

show abstract

Synthesis of Optimal Correction Functions in the Class of Disjunctive Normal Forms

Kabulov,

Baizhumanov,

Saymanov

2024

Mathematics

View full text Add to dashboard Cite

The paper proposes to consider individual heuristics as unreliably operating parts of the information processing system. In a separate case, several different heuristics are adopted to solve the same problem, and the results obtained are adjusted in a certain way. In this case, problems arise that are close in methodology to the problems of synthesizing reliable circuits from unreliable elements or making a collective expert decision. The work solves the problem of constructing an optimal correction function based on control material; classes of functions of k-valued logic under monotonicity restrictions are studied. A theorem on the completeness of the class of monotonic functions of k-valued logic for arbitrary k is proved, and a basis in the given class is proved and constructed. The problem of constructing an optimal corrector in the class of disjunctive normal forms of k-valued functions is solved.

show abstract

Deterministic solution of algebraic equations in sentiment analysis

Cited by 3 publications

References 82 publications

Algebraic Recognition Approach in IoT Ecosystem

Algebraic Recognition Approach in IoT Ecosystem

A Hybrid Hierarchical Mathematical Heuristic Solution of Sparse Algebraic Equations in Sentiment Analysis

Synthesis of Optimal Correction Functions in the Class of Disjunctive Normal Forms

Contact Info

Product

Resources

About