scholarly journals Few-Shot Adaptation for Multimedia Semantic Indexing

2018 ◽  
Author(s):  
Nakamasa Inoue ◽  
Koichi Shinoda
Keyword(s):  
Semantic Indexing

SOAF: Semantic Indexing System Based on Collaborative Tagging

10.28945/371 ◽  
2008 ◽  
Vol 4 ◽  
pp. 137-149 ◽  
Author(s):  
Doina Ana Cernea ◽  
Esther Del Moral-Pérez ◽  
Jose E. Labra Gayo
Keyword(s):  
Semantic Indexing ◽  
Collaborative Tagging ◽  
Indexing System

Analyzing Large-Scale Proteomics Projects with Latent Semantic Indexing

2008 ◽  
Vol 7 (1) ◽  
pp. 182-191 ◽  
Author(s):  
Sebastian Klie ◽  
Lennart Martens ◽  
Juan Antonio Vizcaíno ◽  
Richard Côté ◽  
Phil Jones ◽  
...  
Keyword(s):  
Large Scale ◽  
Latent Semantic Indexing ◽  
Semantic Indexing

A Method Based on Support Vector Machine for Feature Selection of Latent Semantic Features

2011 ◽  
Vol 181-182 ◽  
pp. 830-835
Author(s):  
Min Song Li
Keyword(s):  
Support Vector Machine ◽  
Text Categorization ◽  
Latent Semantic Indexing ◽  
Classification Performance ◽  
Compact Representation ◽  
Support Vector ◽  
Semantic Features ◽  
Semantic Indexing ◽  
Feature Extraction Method ◽  
Feature Subspace

Latent Semantic Indexing(LSI) is an effective feature extraction method which can capture the underlying latent semantic structure between words in documents. However, it is probably not the most appropriate for text categorization to use the method to select feature subspace, since the method orders extracted features according to their variance,not the classification power. We proposed a method based on support vector machine to extract features and select a Latent Semantic Indexing that be suited for classification. Experimental results indicate that the method improves classification performance with more compact representation.

Biomedical Document Clustering Based on Accelerated Symbiotic Organisms Search Algorithm

2021 ◽  
Vol 12 (4) ◽  
pp. 169-185
Author(s):  
Saida Ishak Boushaki ◽  
Omar Bendjeghaba ◽  
Nadjet Kamel
Keyword(s):  
Clustering Algorithm ◽  
Search Algorithm ◽  
Clustering Algorithms ◽  
Document Clustering ◽  
Latent Semantic Indexing ◽  
Research Area ◽  
Semantic Indexing ◽  
Local Optima ◽  
Symbiotic Organisms Search ◽  
Symbiotic Organisms

Clustering is an important unsupervised analysis technique for big data mining. It finds its application in several domains including biomedical documents of the MEDLINE database. Document clustering algorithms based on metaheuristics is an active research area. However, these algorithms suffer from the problems of getting trapped in local optima, need many parameters to adjust, and the documents should be indexed by a high dimensionality matrix using the traditional vector space model. In order to overcome these limitations, in this paper a new documents clustering algorithm (ASOS-LSI) with no parameters is proposed. It is based on the recent symbiotic organisms search metaheuristic (SOS) and enhanced by an acceleration technique. Furthermore, the documents are represented by semantic indexing based on the famous latent semantic indexing (LSI). Conducted experiments on well-known biomedical documents datasets show the significant superiority of ASOS-LSI over five famous algorithms in terms of compactness, f-measure, purity, misclassified documents, entropy, and runtime.

scholarly journals Adaptive business rules framework for workflow management

2019 ◽  
Vol 25 (5) ◽  
pp. 948-971
Author(s):  
Kanana Ezekiel ◽  
Vassil Vassilev ◽  
Karim Ouazzane ◽  
Yogesh Patel
Keyword(s):  
Real Time ◽  
Business Process ◽  
Business Processes ◽  
Object Oriented ◽  
Process Modelling ◽  
Semantic Indexing ◽  
Business Rules ◽  
Business Process Modelling ◽  
Bottom Up ◽  
Content Type

Purpose Changing scattered and dynamic business rules in business workflow systems has become a growing problem that hinders the use and configuration of workflow-based applications. There is a gap in the existing research studies which currently focus on solutions that are application specific, without accounting for the universal logical dependencies between the business rules and, as a result, do not support adaptation of the business rules in real time. The paper aims to discuss this issue. Design/methodology/approach To tackle the above problems, this paper adopts a bottom-up approach, which puts forward a component model of the business process workflows and then adds business rules which have clear logical semantics. This allows incremental development of the workflows and semantic indexing of the rules which govern them during the initial acquisition. Findings The paper introduces an event-driven model for development of business workflows which is purely logic-based and can be easily implemented using an object-oriented technology, together with a model of the business rules dependencies which supports incremental semantic indexing. It also proposes a two-level inference mechanism as a vehicle for controlling the business process execution and the process of adaptation of the business rules at real time based on propagating the dependencies. Research limitations/implications The framework is strictly logical and completely domain-independent. It allows to account both synchronous and asynchronous triggering events as well as both qualitative and quantitative description of the conditions of the rules. Although our primary interest is to apply the framework to the business processes typical in the construction industry we believe our approach has much wider potential due to its strictly logical formalization and domain independence. In fact it can be used to control any business processes where the execution is governed by rules. Practical implications The framework could be applied to both large business process modelling tasks and small but very dynamic business processes like the typical digital business processes found in online banking or e-Commerce. For example, it can be used for adjusting security policies by adding the capability to adapt automatically the access rights to account for additional resources and new channels of operation which can be very interesting ion both B2C and B2B applications. Social implications The potential scope of the impact of the research reported here is linked to the wide applicability of rule-based systems in business. Our approach makes it possible not only to control the execution of the processes, but also to identify problems in the control policies themselves from the point of view of their logical properties – consistency, redundancies and potential gaps in the logics. In addition to this, our approach not only increases the efficiency, but also provides flexibility for adaptation of the policies in real time and increases the security of the overall control which improves the overall quality of the automation. Originality/value The major achievement reported in this paper is the construction of a universal, strictly logic-based event-driven framework for business process modelling and control, which allows purely logical analysis and adaptation of the business rules governing the business workflows through accounting their dependencies. An added value is the support for object-oriented implementation and the incremental indexing which has been possible thanks to the bottom-up approach adopted in the construction of the framework.

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