This document summarizes a research paper about developing a system called ShopIT that assists online shoppers in navigating shopping websites more efficiently based on their preferences. ShopIT uses a top-k algorithm to compute and suggest the top-k highest ranked navigation flows based on user-specified criteria and ranking metrics. It models websites as directed acyclic graphs and navigation flows as sequences of activity implementations. ShopIT adapts its suggestions in response to user choices during navigation to provide a personalized experience. The system was found to outperform other ranking systems in optimizing user navigation cost.
Agent based P ersonalized e - Catalog S ervice S ystemEditor IJCATR
With the emergence of the e
-
Catalog, there has been an increasingly wide application of commodities query in distribut
ed
environment in the field of e
-
commerce. But e
-
Catalog is often autonomous and heterogeneous, effectively integrating and querying
them is a delicate and time
-
consuming task. Electronic catalog contains rich semantics associated with products, and serves
as a
challenging domain for ontology application. Ontology is concerned with the nature and relations of being. It can play a cruc
ial role
in e
-
commerce as a formalization of e
-
Catalog. User personalized catalog ontology aims at capturing the users' inter
ests in a working
domain, which forms the basis of providing personalized e
-
Catalog services.
This paper describes a prototype of an ontology
-
based
Information retrieval agent.
User personalized catalog ontology aims at capturing the users' interests in a
working domain, which
forms the basis of providing personalized e
-
Catalog services.
In this paper, we present an ontological model of e
-
Catalogs, and design
an Agent based personalized e
-
Catalog service system (ABPECSS), which achieves match user personal
ized catalog ontology and
domain e
-
Catalog ontology based on ontology integrated
System For Product Recommendation In E-Commerce ApplicationsIJERD Editor
This document summarizes a research paper that proposes a personalized hybrid recommendation system for e-commerce applications that can support massive datasets. The system uses clustering algorithms to build a user preference tree to model user interests. It then uses map-reduce on Hadoop to accelerate the recommendation algorithm using user and product similarity matrices in order to provide recommendations to users in an online mode quickly despite large, unstructured data. The performance of the map-reduce based system is analyzed and shown to have advantages over traditional centralized methods for large datasets.
IJERD (www.ijerd.com) International Journal of Engineering Research and Devel...IJERD Editor
This document summarizes a study that aimed to identify value co-creation attributes that influence the UTM Institutional Repository (UTM IR), an e-service application. The study used interviews with UTM IR providers and users to collect data on the e-service based on the DART model of value co-creation. The DART model examines dialogue, access, risk, and transparency between customers and providers. Interview responses were coded according to the DART building blocks. A gap analysis of the coded provider and user responses identified attributes influencing the UTM IR from a value co-creation perspective. The findings aimed to help evaluate the UTM IR e-service based on customer and provider value co-creation.
This document proposes a needs assessment approach to product bundling in retail banking. It involves understanding customer needs through a questionnaire, analyzing the responses using business rules, and recommending product bundles. A multi-layered, service-oriented architecture is proposed to implement needs assessment across delivery channels like internet, mobile, and branch banking. The approach could help banks better understand customer needs and offer customized product bundles.
IRJET- Analysis on Existing Methodologies of User Service Rating Prediction S...IRJET Journal
This document summarizes and analyzes existing methodologies for user service rating prediction systems. It discusses recommendation systems including collaborative filtering, content-based filtering, and hybrid approaches. Collaborative filtering predicts user ratings based on opinions of other similar users but faces challenges of cold start, scalability, and sparsity. Content-based filtering relies on item profiles and user preferences to recommend similar items but requires detailed item information. Hybrid systems combine collaborative and content-based filtering to address their individual limitations. The document also examines social recommender systems and how they can account for relationship strength, expertise, and user similarity within social networks.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
The document describes an online shopping cart system. It includes sections on the system scope, software requirements specification, functional model using data flow diagrams, activity diagrams showing the customer workflow, and a use case diagram showing actors and use cases. The functional model section includes data flow diagrams for the overall system, product listing, administrator, and secure gateway provider. The activity diagram shows the customer's shopping, checkout, and order cancellation processes. The use case diagram identifies the customer and purchased item as actors and use cases for viewing products, purchasing an item, and cancelling an order.
The document describes a multi-channel recommender system model to recommend questions to potential answerers on Yahoo! Answers. It uses question attributes like text, categories, and user interactions, and user attributes like interaction channels and explicit preferences. Interaction features are created by matching question and user attributes, and bias features address intuitions like answered vs. unanswered questions. The model is trained on Gradient Boosted Decision Trees and evaluated against baselines that differently weight interaction channels.
Agent based P ersonalized e - Catalog S ervice S ystemEditor IJCATR
With the emergence of the e
-
Catalog, there has been an increasingly wide application of commodities query in distribut
ed
environment in the field of e
-
commerce. But e
-
Catalog is often autonomous and heterogeneous, effectively integrating and querying
them is a delicate and time
-
consuming task. Electronic catalog contains rich semantics associated with products, and serves
as a
challenging domain for ontology application. Ontology is concerned with the nature and relations of being. It can play a cruc
ial role
in e
-
commerce as a formalization of e
-
Catalog. User personalized catalog ontology aims at capturing the users' inter
ests in a working
domain, which forms the basis of providing personalized e
-
Catalog services.
This paper describes a prototype of an ontology
-
based
Information retrieval agent.
User personalized catalog ontology aims at capturing the users' interests in a
working domain, which
forms the basis of providing personalized e
-
Catalog services.
In this paper, we present an ontological model of e
-
Catalogs, and design
an Agent based personalized e
-
Catalog service system (ABPECSS), which achieves match user personal
ized catalog ontology and
domain e
-
Catalog ontology based on ontology integrated
System For Product Recommendation In E-Commerce ApplicationsIJERD Editor
This document summarizes a research paper that proposes a personalized hybrid recommendation system for e-commerce applications that can support massive datasets. The system uses clustering algorithms to build a user preference tree to model user interests. It then uses map-reduce on Hadoop to accelerate the recommendation algorithm using user and product similarity matrices in order to provide recommendations to users in an online mode quickly despite large, unstructured data. The performance of the map-reduce based system is analyzed and shown to have advantages over traditional centralized methods for large datasets.
IJERD (www.ijerd.com) International Journal of Engineering Research and Devel...IJERD Editor
This document summarizes a study that aimed to identify value co-creation attributes that influence the UTM Institutional Repository (UTM IR), an e-service application. The study used interviews with UTM IR providers and users to collect data on the e-service based on the DART model of value co-creation. The DART model examines dialogue, access, risk, and transparency between customers and providers. Interview responses were coded according to the DART building blocks. A gap analysis of the coded provider and user responses identified attributes influencing the UTM IR from a value co-creation perspective. The findings aimed to help evaluate the UTM IR e-service based on customer and provider value co-creation.
This document proposes a needs assessment approach to product bundling in retail banking. It involves understanding customer needs through a questionnaire, analyzing the responses using business rules, and recommending product bundles. A multi-layered, service-oriented architecture is proposed to implement needs assessment across delivery channels like internet, mobile, and branch banking. The approach could help banks better understand customer needs and offer customized product bundles.
IRJET- Analysis on Existing Methodologies of User Service Rating Prediction S...IRJET Journal
This document summarizes and analyzes existing methodologies for user service rating prediction systems. It discusses recommendation systems including collaborative filtering, content-based filtering, and hybrid approaches. Collaborative filtering predicts user ratings based on opinions of other similar users but faces challenges of cold start, scalability, and sparsity. Content-based filtering relies on item profiles and user preferences to recommend similar items but requires detailed item information. Hybrid systems combine collaborative and content-based filtering to address their individual limitations. The document also examines social recommender systems and how they can account for relationship strength, expertise, and user similarity within social networks.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
The document describes an online shopping cart system. It includes sections on the system scope, software requirements specification, functional model using data flow diagrams, activity diagrams showing the customer workflow, and a use case diagram showing actors and use cases. The functional model section includes data flow diagrams for the overall system, product listing, administrator, and secure gateway provider. The activity diagram shows the customer's shopping, checkout, and order cancellation processes. The use case diagram identifies the customer and purchased item as actors and use cases for viewing products, purchasing an item, and cancelling an order.
The document describes a multi-channel recommender system model to recommend questions to potential answerers on Yahoo! Answers. It uses question attributes like text, categories, and user interactions, and user attributes like interaction channels and explicit preferences. Interaction features are created by matching question and user attributes, and bias features address intuitions like answered vs. unanswered questions. The model is trained on Gradient Boosted Decision Trees and evaluated against baselines that differently weight interaction channels.
Recommendation systems only provide more specific recommendations to users. They do not consider
giving a justification for the recommendation. However, the justification for the recommendation allows the
user to make the decision whether or not to accept the recommendation. It also improves user satisfaction
and the relevance of the recommended item. However, the IAAS recommendation system that uses
advisories to make recommendations does not provide a justification for the recommendations. That is why
in this article, our task consists for helping IAAS users to justify their recommendations.
1. The document discusses various IEEE 2012-2013 software projects in domains like Java, J2ME, J2EE, .NET, MATLAB and NS2.
2. SBGC provides technical guidance and support for students' IEEE projects, including project reports, materials, certificates etc.
3. A variety of IEEE projects are offered for students from different engineering departments like ECE, EEE, CSE etc. and levels like B.E, M.Tech, MBA.
This document discusses analyzing a movie recommendation system using the MovieLens dataset. It compares user-based and item-based collaborative filtering approaches. For user-based filtering, it calculates user similarity using cosine similarity and predicts ratings. For item-based filtering, it also uses cosine similarity to find similar items and predicts ratings. It evaluates the performance of both approaches using root mean square deviation and finds that item-based collaborative filtering has lower error compared to user-based filtering.
IRJET- E-Commerce Recommendation based on Users Rating DataIRJET Journal
This document proposes a recommendation system for e-commerce called SBT-Rec that is based on structural balance theory. It aims to address challenges with sparse user rating data where traditional collaborative filtering may not find similar users or items. SBT-Rec first identifies a target user's "enemies" or opposite preferences, then determines "possible friends" according to the rule that "an enemy of my enemy is my friend". It recommends items preferred by these possible friends. It also identifies "possibly similar items" for a target user's preferred items using the same rule. The document outlines the SBT-Rec algorithm and describes its architecture which collects data, performs recommendation, and provides a user interface.
This document discusses a navigation cost modeling technique based on ontology for effective navigation of query results from large datasets. It presents an approach that uses concept hierarchies built from annotated data to categorize results and reduce the navigation cost for users. An initial navigation tree is constructed from the dataset ontology and refined by removing empty nodes. The tree is then dynamically expanded at certain points to minimize the user's navigation cost and quickly reach the desired results.
Paper Gloria Cea - Goal-Oriented Design Methodology Applied to User Interface...WTHS
This document describes a user interface designed for a mobile application called the Functional Assessment System (FAS). The FAS allows users to assess their aerobic fitness on their own without specialized equipment. The design of the mobile application interface was guided by the Goal-Oriented Design methodology. This methodology focuses on representing users as characters with specific goals and designing scenarios to help users achieve those goals. The document also discusses evaluating the usability of the interface using the AttrakDiff questionnaire to assess pragmatic and hedonic qualities. The results showed satisfactory user interaction with the FAS mobile application interface.
This document summarizes several research papers on improving recommendation systems using item-based collaborative filtering approaches. It discusses challenges with traditional collaborative filtering like data sparsity and scalability. It then summarizes various item-based recommendation algorithms that analyze item relationships to indirectly compute recommendations. These include item-item similarity techniques like cosine similarity and adjusting for average ratings. The document also reviews literature on combining item categories and interestingness measures to improve accuracy. Overall, it analyzes different item-based collaborative filtering techniques to address challenges and provide high quality, personalized recommendations at scale.
This document summarizes a study that compares the performance of the MAC layer in flat and hierarchical mobile ad hoc networks (MANETs). The study uses simulation to analyze throughput and packet drops. It finds that throughput is the same for both network structures, but that hierarchical networks have fewer packet drops at the MAC layer. Specifically, packet drops only occurred at 3 nodes in the hierarchical network, whereas 14 nodes experienced drops in the flat network structure. Therefore, the hierarchical approach improves MAC layer performance by reducing packet drops.
The document reviews the effects of refrigerant properties on system performance comparison. It discusses key properties like density, viscosity, thermal conductivity, and critical temperature. A high COP requires properties like high latent heat, liquid thermal conductivity, and vapor density, with low liquid viscosity and molecular weight. Critical temperature and heat capacity involve a trade-off between capacity and COP. The presence of oil can impact heat transfer coefficients and pressure drops depending on the amount and solubility. Key derived parameters like volumetric capacity and heat transfer coefficients also influence system performance. Properties like normal boiling point, critical temperature, liquid thermal conductivity, and vapor density have the most significant impacts.
This document discusses a proposed five-factor authentication scheme for secure banking transactions. The five factors are RFID card, PIN number, fingerprint, one-time password (OTP), and keypad ID. During registration, users provide fingerprints and other information that is stored. For login, the user submits their RFID card, PIN, and fingerprint. If the fingerprint exactly matches, the transaction is allowed. If not, an OTP is sent to the user's phone for verification along with keypad ID before allowing the transaction. The scheme aims to improve security over three-factor authentication while protecting user privacy.
This document summarizes experiments conducted on a tube settler to treat filter backwash (FBW) water from a conventional water treatment plant. The experiments aimed to optimize plant operation and reduce residual waste. Characterization of the FBW water found it contained high solids and bacteria. Experiments on a laboratory-scale tube settler showed optimum settling velocities for treating FBW water both with and without additional treatment. Characterization of FBW sludge found it suitable for use in brick making when mixed with clay at 25% by volume, meeting strength standards. Operational modifications to rapid sand filters and backwashing reduced FBW volumes by 18%.
This document summarizes a research paper about implementing self-healing mechanisms to protect against control flow attacks in wireless sensor networks. The paper proposes an access control scheme that can detect attempts to alter the control flow of sensor applications and then recover the sensor data. It processes application code at the machine instruction level rather than analyzing source code. The implementation shows that the self-healing scheme is lightweight and can effectively protect sensor applications from control flow attacks by enforcing access control, providing self-healing recovery, and diversifying code images across sensors.
This document summarizes a technique called CADU (collaborative adaptive down-sampling and upconversion) to improve image compression at low bit rates. The technique adaptively decreases high frequency information by directionally prefiltering an image before uniform downsampling. This allows the downsampled image to be conventionally compressed while avoiding aliasing artifacts. At the decoder, the low-resolution image is decompressed and then upconverted to the original resolution using constrained least squares restoration with an autoregressive model. Experimental results show CADU outperforms JPEG2000 in PSNR and visual quality at low to medium bit rates. The technique suggests oversampling wastes resources and could hurt quality given tight bit budgets.
1) The document describes a proposed hybrid power generation system using solar, wind, and hydro energy sources.
2) It presents models for the photovoltaic cells, wind turbine generator, and hydraulic turbine components and discusses how they are combined and controlled.
3) Simulation results are shown verifying the system can provide continuous power to loads by compensating for periods of low solar or wind input using hydro power generation.
This document presents a proposed algorithm for public key cryptography using matrices. The algorithm has three stages: 1) shuffling the original data using a linear congruential method and arranging it in a matrix, 2) traversing the data matrix in different patterns, and 3) generating a system of non-homogeneous linear equations from the matrix to derive private keys. The algorithm aims to provide data confidentiality, integrity and authentication for cloud computing applications using public key cryptography with matrices in a way that has constant complexity regardless of key size.
This document summarizes a research paper that introduces a novel multi-viewpoint similarity measure for clustering text documents. The paper begins with background on commonly used similarity measures like Euclidean distance and cosine similarity. It then presents the novel multi-viewpoint measure, which considers multiple viewpoints (objects not assumed to be in the same cluster) rather than a single viewpoint. The paper proposes two new clustering criterion functions based on this measure and compares them to other algorithms on benchmark datasets. The goal is to develop a similarity measure and clustering methods that provide high-quality, consistent performance like k-means but can better handle sparse, high-dimensional text data.
Fabiano é um homem pobre e ignorante que vive no sertão nordestino com sua família. Eles passam por muitas dificuldades tentando sobreviver à seca, incluindo fome, doenças e exploração. Apesar disso, Fabiano mantém sua honestidade e esperança em dias melhores.
El documento contiene la descripción de 33 códigos (cod. NAT 01-33) de láminas decorativas de temática natural producidas por Woopadiseno. Para cada código se especifica el tamaño, número de láminas, colores y contacto de la empresa productora.
Recommendation systems only provide more specific recommendations to users. They do not consider
giving a justification for the recommendation. However, the justification for the recommendation allows the
user to make the decision whether or not to accept the recommendation. It also improves user satisfaction
and the relevance of the recommended item. However, the IAAS recommendation system that uses
advisories to make recommendations does not provide a justification for the recommendations. That is why
in this article, our task consists for helping IAAS users to justify their recommendations.
1. The document discusses various IEEE 2012-2013 software projects in domains like Java, J2ME, J2EE, .NET, MATLAB and NS2.
2. SBGC provides technical guidance and support for students' IEEE projects, including project reports, materials, certificates etc.
3. A variety of IEEE projects are offered for students from different engineering departments like ECE, EEE, CSE etc. and levels like B.E, M.Tech, MBA.
This document discusses analyzing a movie recommendation system using the MovieLens dataset. It compares user-based and item-based collaborative filtering approaches. For user-based filtering, it calculates user similarity using cosine similarity and predicts ratings. For item-based filtering, it also uses cosine similarity to find similar items and predicts ratings. It evaluates the performance of both approaches using root mean square deviation and finds that item-based collaborative filtering has lower error compared to user-based filtering.
IRJET- E-Commerce Recommendation based on Users Rating DataIRJET Journal
This document proposes a recommendation system for e-commerce called SBT-Rec that is based on structural balance theory. It aims to address challenges with sparse user rating data where traditional collaborative filtering may not find similar users or items. SBT-Rec first identifies a target user's "enemies" or opposite preferences, then determines "possible friends" according to the rule that "an enemy of my enemy is my friend". It recommends items preferred by these possible friends. It also identifies "possibly similar items" for a target user's preferred items using the same rule. The document outlines the SBT-Rec algorithm and describes its architecture which collects data, performs recommendation, and provides a user interface.
This document discusses a navigation cost modeling technique based on ontology for effective navigation of query results from large datasets. It presents an approach that uses concept hierarchies built from annotated data to categorize results and reduce the navigation cost for users. An initial navigation tree is constructed from the dataset ontology and refined by removing empty nodes. The tree is then dynamically expanded at certain points to minimize the user's navigation cost and quickly reach the desired results.
Paper Gloria Cea - Goal-Oriented Design Methodology Applied to User Interface...WTHS
This document describes a user interface designed for a mobile application called the Functional Assessment System (FAS). The FAS allows users to assess their aerobic fitness on their own without specialized equipment. The design of the mobile application interface was guided by the Goal-Oriented Design methodology. This methodology focuses on representing users as characters with specific goals and designing scenarios to help users achieve those goals. The document also discusses evaluating the usability of the interface using the AttrakDiff questionnaire to assess pragmatic and hedonic qualities. The results showed satisfactory user interaction with the FAS mobile application interface.
This document summarizes several research papers on improving recommendation systems using item-based collaborative filtering approaches. It discusses challenges with traditional collaborative filtering like data sparsity and scalability. It then summarizes various item-based recommendation algorithms that analyze item relationships to indirectly compute recommendations. These include item-item similarity techniques like cosine similarity and adjusting for average ratings. The document also reviews literature on combining item categories and interestingness measures to improve accuracy. Overall, it analyzes different item-based collaborative filtering techniques to address challenges and provide high quality, personalized recommendations at scale.
This document summarizes a study that compares the performance of the MAC layer in flat and hierarchical mobile ad hoc networks (MANETs). The study uses simulation to analyze throughput and packet drops. It finds that throughput is the same for both network structures, but that hierarchical networks have fewer packet drops at the MAC layer. Specifically, packet drops only occurred at 3 nodes in the hierarchical network, whereas 14 nodes experienced drops in the flat network structure. Therefore, the hierarchical approach improves MAC layer performance by reducing packet drops.
The document reviews the effects of refrigerant properties on system performance comparison. It discusses key properties like density, viscosity, thermal conductivity, and critical temperature. A high COP requires properties like high latent heat, liquid thermal conductivity, and vapor density, with low liquid viscosity and molecular weight. Critical temperature and heat capacity involve a trade-off between capacity and COP. The presence of oil can impact heat transfer coefficients and pressure drops depending on the amount and solubility. Key derived parameters like volumetric capacity and heat transfer coefficients also influence system performance. Properties like normal boiling point, critical temperature, liquid thermal conductivity, and vapor density have the most significant impacts.
This document discusses a proposed five-factor authentication scheme for secure banking transactions. The five factors are RFID card, PIN number, fingerprint, one-time password (OTP), and keypad ID. During registration, users provide fingerprints and other information that is stored. For login, the user submits their RFID card, PIN, and fingerprint. If the fingerprint exactly matches, the transaction is allowed. If not, an OTP is sent to the user's phone for verification along with keypad ID before allowing the transaction. The scheme aims to improve security over three-factor authentication while protecting user privacy.
This document summarizes experiments conducted on a tube settler to treat filter backwash (FBW) water from a conventional water treatment plant. The experiments aimed to optimize plant operation and reduce residual waste. Characterization of the FBW water found it contained high solids and bacteria. Experiments on a laboratory-scale tube settler showed optimum settling velocities for treating FBW water both with and without additional treatment. Characterization of FBW sludge found it suitable for use in brick making when mixed with clay at 25% by volume, meeting strength standards. Operational modifications to rapid sand filters and backwashing reduced FBW volumes by 18%.
This document summarizes a research paper about implementing self-healing mechanisms to protect against control flow attacks in wireless sensor networks. The paper proposes an access control scheme that can detect attempts to alter the control flow of sensor applications and then recover the sensor data. It processes application code at the machine instruction level rather than analyzing source code. The implementation shows that the self-healing scheme is lightweight and can effectively protect sensor applications from control flow attacks by enforcing access control, providing self-healing recovery, and diversifying code images across sensors.
This document summarizes a technique called CADU (collaborative adaptive down-sampling and upconversion) to improve image compression at low bit rates. The technique adaptively decreases high frequency information by directionally prefiltering an image before uniform downsampling. This allows the downsampled image to be conventionally compressed while avoiding aliasing artifacts. At the decoder, the low-resolution image is decompressed and then upconverted to the original resolution using constrained least squares restoration with an autoregressive model. Experimental results show CADU outperforms JPEG2000 in PSNR and visual quality at low to medium bit rates. The technique suggests oversampling wastes resources and could hurt quality given tight bit budgets.
1) The document describes a proposed hybrid power generation system using solar, wind, and hydro energy sources.
2) It presents models for the photovoltaic cells, wind turbine generator, and hydraulic turbine components and discusses how they are combined and controlled.
3) Simulation results are shown verifying the system can provide continuous power to loads by compensating for periods of low solar or wind input using hydro power generation.
This document presents a proposed algorithm for public key cryptography using matrices. The algorithm has three stages: 1) shuffling the original data using a linear congruential method and arranging it in a matrix, 2) traversing the data matrix in different patterns, and 3) generating a system of non-homogeneous linear equations from the matrix to derive private keys. The algorithm aims to provide data confidentiality, integrity and authentication for cloud computing applications using public key cryptography with matrices in a way that has constant complexity regardless of key size.
This document summarizes a research paper that introduces a novel multi-viewpoint similarity measure for clustering text documents. The paper begins with background on commonly used similarity measures like Euclidean distance and cosine similarity. It then presents the novel multi-viewpoint measure, which considers multiple viewpoints (objects not assumed to be in the same cluster) rather than a single viewpoint. The paper proposes two new clustering criterion functions based on this measure and compares them to other algorithms on benchmark datasets. The goal is to develop a similarity measure and clustering methods that provide high-quality, consistent performance like k-means but can better handle sparse, high-dimensional text data.
Fabiano é um homem pobre e ignorante que vive no sertão nordestino com sua família. Eles passam por muitas dificuldades tentando sobreviver à seca, incluindo fome, doenças e exploração. Apesar disso, Fabiano mantém sua honestidade e esperança em dias melhores.
El documento contiene la descripción de 33 códigos (cod. NAT 01-33) de láminas decorativas de temática natural producidas por Woopadiseno. Para cada código se especifica el tamaño, número de láminas, colores y contacto de la empresa productora.
Este documento apresenta os detalhes de um negócio de venda direta de produtos de beleza, incluindo perfumaria. Descreve a empresa, os produtos, o mercado-alvo e as diferentes formas como os distribuidores podem ganhar dinheiro vendendo os produtos e recrutando novos distribuidores.
El documento fue escrito por María Olazábal Viganó. Trata sobre una persona llamada Arantxa. No proporciona más detalles sobre el contenido o tema del documento.
This C program implements a deque (double-ended queue) using a linked list. The deque supports the basic operations of initialization, checking for emptiness, adding/removing elements from the front/rear, and printing the elements. Functions are defined to initialize the deque, check if it is empty, add elements to the front/rear, remove elements from the front/rear, and print the elements. These functions are used in main() to demonstrate adding/removing elements from both ends and printing the deque.
El documento discute el impacto de las tecnologías de la información y la comunicación (TIC) en el desarrollo y las oportunidades. Señala que el acceso a las TIC brinda oportunidades de desarrollo, pero también existen brechas digitales en el acceso y la alfabetización digital que dificultan su uso efectivo. Propone capacitación y el uso adecuado de los recursos para superar estas brechas y aprovechar mejor el potencial de las TIC.
O documento discute os conceitos de liberdade e inexorabilidade. Afirma que a liberdade humana é o livre arbítrio e está sujeita à responsabilidade, enquanto a inexorabilidade é aquilo que está fora de nosso controle. Também apresenta condições para o exercício responsável da liberdade, como autocontrole e consideração das consequências dos atos.
Providing Highly Accurate Service Recommendation over Big Data using Adaptive...IRJET Journal
This document proposes an adaptive recommendation system to provide accurate service recommendations over big data. It combines content-based, item-based, and knowledge-based recommendation techniques using an adaptive collaborative filtering approach. The system aims to improve scalability, accuracy, and address cold-start problems. It uses clustering to group similar services together to reduce data size and improve recommendation accuracy. The system architecture includes administrative and visitor modules to manage products and provide recommendations respectively. Service recommendations are generated by matching users to similar neighborhoods based on item preferences.
IRJET- An Integrated Recommendation System using Graph Database and QGISIRJET Journal
This document presents a recommendation system that uses a graph database and QGIS to find the shortest path for a user to shop at the nearest mall. It analyzes product reviews stored in the Neo4j graph database to determine which products the user may be interested in. It then uses QGIS to calculate the shortest distance from the user's current location to the nearest mall with the recommended products. The system aims to minimize the time a user spends shopping by providing personalized recommendations and routing them to the closest appropriate location. It discusses how graph databases and hybrid recommendation approaches can be used to integrate different recommendation techniques for improved performance.
The document proposes a finger gesture-based rating system using computer vision and cloud computing. The system would allow customers to provide ratings for products and services by holding up a corresponding number of fingers, from 1 to 5. Computer vision techniques would recognize the gesture and record the rating in a collective database in the cloud. This universal database could then provide aggregated rating data across multiple companies for improved analytics. The system aims to provide a more efficient and engaging way for customers to submit feedback compared to traditional rating methods.
Enactment of Firefly Algorithm and Fuzzy C-Means Clustering For Consumer Requ...IRJET Journal
The document proposes a novel methodology for predicting consumer demand and future requests on web pages using a hybrid approach. It first classifies consumers as potential or non-potential using a firefly-based neural network with Levenberg-Marquardt algorithm. Potential consumer data is then clustered using an improved fuzzy C-means clustering algorithm. Finally, upcoming consumer demand is predicted by analyzing patterns and recommending web pages with higher weights. The proposed approach is implemented in Java and CloudSim and aims to overcome limitations of existing recommendation systems by providing more accurate and efficient predictions in shorter time.
This document describes a book recommendation system that uses collaborative filtering and content-based filtering techniques. It provides an overview of how collaborative filtering, content-based filtering, and hybrid recommendation systems work. For collaborative filtering, it discusses user-based and item-based nearest neighbor algorithms. It also outlines some of the advantages and limitations of collaborative filtering, content-based filtering, and hybrid recommendation approaches. The document then presents the architecture of a book recommendation system and describes how it would use a k-nearest neighbors algorithm and weighted rating formulas to make recommendations based on a user's book ratings and similar users' ratings.
The document discusses various software architecture patterns and principles, comparing monolithic and microservices architectures. It covers topics like layers, domain-driven design, code-first versus database-first approaches, and considerations for data management in multi-tenant systems. The key aspects of architectures like microservices and domain-driven design are explained at a high level.
Product Comparison Website using Web scraping and Machine learning.IRJET Journal
This document describes the development of a product comparison website using web scraping and machine learning techniques. The website extracts data like price, features and ratings from multiple e-commerce websites using web scraping. A machine learning algorithm then compares the collected data and provides personalized recommendations to users. The implementation demonstrated that web scraping is effective for collecting product data for comparison. Future work may involve incorporating deep learning models and external data sources to improve recommendations.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology
This document discusses conversational and critique-based recommender systems. It describes three major types of critique-based conversational recommender systems: natural language-based systems, system-suggested critique systems, and user-initiated critique systems. Natural language-based systems interact with users through dialogue to understand preferences, while system-suggested critique systems provide critiques based on product knowledge. The document analyzes advantages and disadvantages of each approach, and proposes a hybrid framework to combine their strengths.
With quick advancement of investigative databases and web data databases are turning out to be exceptionally colossal in size and complex in nature. These databases hold extensive and heterogeneous information, with huge number of relations and qualities. So it is exceptionally hard to outline an arrangement of static inquiry structures to answer different specially appointed database inquirieson these cutting edge databases. Along these lines there is need of such framework which create Query Forms powerfully as indicated by the clients need at run time. The proposed framework Dynamic Query Form i.e.DQF framework going to give an answer by the inquiry interface in extensive and complex databases. In proposed framework, the center idea is to catch client intrigues all through client associations and to adjust the inquiry sort iteratively. Each cycle comprises of 2 sorts of client collaborations: Query Form Enrichment and Query Execution. In Query Form Enrichment DQF would prescribe a positioned rundown of question structure part to client so he/she can choose sought structure segments into current inquiry structure. In Query Execution client fills current inquiry shape and submit question, DQF going to show result and take input from client on gave question results. A client would have office to fill the inquiry frame and submit questions to see the inquiry result at every cycle. So that a question structure could be progressively refined till the client fulfills with the inquiry results.
Detection of Behavior using Machine LearningIRJET Journal
This document discusses using machine learning algorithms to analyze user behavior and predict future behavior based on browsing history data. The researchers collected browsing history data from 20 computers in a lab over various time periods. They extracted features from the data like URL, title, time of visit, and categorized browsing into types like social media, academic, shopping etc. They then trained machine learning models like SVM on 80% of the data and tested it on the remaining 20% to classify users and predict their future behavior. The goal is to develop personalized services and detect anomalies in behavior.
E- learning and Online Shopping Cart Project (integrated with a payment gateway using MySQL Community Server as the data store with Java Server Pages as the delivery mechanism, Struts 2 as the framework and Hibernate 3 as the Object Relational Mapping framework).
• Technology Used : Java Technology, Java Framework (STRUTS 2 AND HIBERNATE 3 ).
• Designing Platform : HTML, JavaScript, CSS, JQuery.
• Development Tool : IDE- NetBeans8.0.
• Client : Babu Banarasi Das University, Lucknow
The document describes a proposed product price comparison website project. The project aims to allow online users to easily compare prices of products across multiple e-commerce websites in one place. It will use web scraping techniques to extract product data, including names, prices and availability from different e-commerce sites. This will help users save time and effort in finding the best deals. The document outlines requirements like collecting and validating product data from different sources in real-time, allowing users to register and receive price alerts. It also evaluates the technical, operational and financial feasibility of the project.
This document provides an overview of web engineering and web application analysis modeling. It discusses the attributes and categories of web applications. It then describes the key elements of the web engineering process including planning, modeling, construction, delivery and evaluation. The document focuses on analysis modeling techniques for web applications including content analysis, interaction analysis, functional analysis, configuration analysis, use case diagrams, sequence diagrams, state diagrams, the interaction model, the functional model and the configuration model. Relationship navigation analysis is also covered. The goal of analysis modeling is to establish a basis for the design of complex web applications.
1. performance testing on web application through hp load1Jatin Aggarwal
Project aimed at providing an extension or enhancement in HP load runner tool which is a software automated testing tool used to carry out the intensive performance testing. The extension aims in designing the functions which is used to reduce the data management time taken by the client or the user in different scripting methods like-parameterization, correlation, and validation checks.
1. PERFORMANCE TESTING ON WEB APPLICATION THROUGH HP LOAD1Jatin Aggarwal
This document discusses performance testing of web applications using the HP LoadRunner tool. It proposes enhancing LoadRunner with functions to reduce the time spent managing data for parameterization, correlation, and validation checks. The techniques are implemented in C and aim to reduce the effort required to parameterize values, saving user time. The paper compares results between the proposed scheme and the existing LoadRunner tool.
The Art and Science of Requirements GatheringVanessa Turke
The document provides an overview of the process for gathering requirements for a project. It discusses the challenges of requirements gathering when stakeholders come from different backgrounds and submit varied documentation. It then outlines eight key steps to improving the requirements gathering process: scoping the project, conducting research, analyzing findings, modeling solutions, validating requirements, negotiating trade-offs, and managing the knowledge gap between experts and new clients. Traditional requirements focus on system operations while user stories emphasize customer value. The overall goal is to achieve consistent documentation that defines the project scope and meets stakeholder needs.
This document proposes a new advanced e-commerce recommendation system that incorporates additional data beyond a user's purchase history to provide improved recommendations. Specifically, it suggests combining a user's search and purchase history with data from social media platforms like Twitter, reviews from sites like Amazon and Snapdeal, the user's location and preferences. This additional data could allow the system to recommend items a user has not previously purchased. It also describes some limitations of existing recommendation systems that only consider purchase history or require clustering users. The proposed system would use clustering and collaborative filtering together to group similar products and then make recommendations based on the evaluations within each cluster to improve accuracy.
A Survey on Recommendation System based on Knowledge Graph and Machine LearningIRJET Journal
This document provides an overview of recommendation systems based on knowledge graphs and machine learning. It first defines key concepts like recommendation systems, knowledge graphs, meta paths, and knowledge graph embedding. It then discusses standard recommendation approaches like content-based filtering, collaborative filtering, and hybrid filtering. The document focuses on knowledge graph-based recommendation systems, how they address issues with traditional approaches, and how machine learning can be used alongside knowledge graphs. It reviews several papers on using knowledge graphs for recommendations and proposes a comparative study. The document also outlines a proposed recommendation system and potential future research directions in the domain.
A Survey on Recommendation System based on Knowledge Graph and Machine Learning
Cd24534538
1. Venkata Ramana Kumari.Ch, B. Sowjanya Rani / International Journal of Engineering Research
and Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 4, July-August 2012, pp.534-538
Query Results Maneuvers using Concept Hierarchies
Venkata Ramana Kumari.Ch 1, B. Sowjanya Rani 2
1
M Tech Student, Dept of CSE, Aditya Engineering College, Surampalem, Andhra Pradesh, India,
2
Assistant Prof, M.Tech, Dept of CSE, Aditya Engineering College, Surampalem, Andhra Pradesh, India,
Abstract:
Search Query Results on large databases user can get a good price by first registering to the
(Pub Med, HPSS, and NERSC) often return a store’s customers club. After passing through some
large number of results of which only a small advertisement page that provides such members with
subset is relevant to the end user. To reduce this discount coupons, and finally buying a certain set of
information overload Ranking and categorization components (including a certain Intel processor) that,
were developed earlier. Efficient navigation when purchased together with the above coupons,
through results categorization and annotations is yields the cheapest overall price. Clearly, the user
the focus of this paper. In this paper, we present a might be interested in knowing this information if she
new system based on online shopping that is after the deal with the best price [9]. Alternatively,
implement the Top-K algorithm. This system the user may prefer combinations where the delivery
assists that on-line shoppers navigated in most time is minimal, or may want to use the experience of
effective paths based on their specified criteria others and view the most popular navigation paths.
and preferences. The suggestions are continually We present here ShopIT (Shopping
adapted to choices/decisions taken by the users assistant); a system which suggests the most effective
while navigating. Earlier works expand the navigation paths based on preferences and specified
hierarchy in a predefined static approach, without criteria. When the user starts her navigation in the
stressing on navigation cost. We show site, she may specify her constraints and her ranking
experimentally that the system outperforms state- function of interest, and have the system compute and
of-the-art categorization systems with respect to propose (an initial set of) top-k ranked navigation
the user navigation cost. We present an flows[2], out of these conforming to the constraints.
experimental study that our algorithm The user then continues her navigation taking into
outperforms state-of-the-art ranking systems with account the presented recommendations, but may
respect to the navigation flow. also make choices different than those proposed by
the system.
Index Terms: Pub Med, Top-k algorithm, Effective
Navigation, Ranking, and Categorization etc. Several challenges arise in the development
of such a system. First, the number of possible
I INTRODUCTION navigation flows in a given web-site is not only large
On-line shopping is extremely popular but infinite, as users may navigate back and forth
nowadays, with millions of users purchasing products between pages. Hence, enumerating and ranking all
in shops that provide a Web interface. It is common relevant flows is clearly not an option. Second, it is
for on-line shops to offer a vast number of product critical to maintain a fast response time in order to
Options and combinations thereof [4]. This is very provide a pleasant user experience. Finally, as
useful but, at the same time, makes shopping rather explained above, the computation must be flexible
confusing. It is often very difficult to and the specific and adaptive, to account for run-time user choices
navigation path in the site that will lead to an and our algorithm is optimal [2] and very efficient.
“optimal” result, best suiting the needs and
preferences of the given user.
II TECHNICAL BACKGROUND
We provide in this section some background
Consider for example an on-line store which
on our model for Web applications and for queries
offers various processors, screens etc; that allows
over such applications.
users to assemble computers from a variety of
Web-based Applications: Our model for Web
component parts. Consider a user that is interested in
applications, introduced in [1,6], abstractly models
buying a cheap Intel processor computer. Suppose
applications as a set of (nested) DAGs - Directed A
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2. Venkata Ramana Kumari.Ch, B. Sowjanya Rani / International Journal of Engineering Research
and Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 4, July-August 2012, pp.534-538
cyclic Graphs - each intuitively is corresponding to a the original query, and an efficient adaptive
specific function or service[1,3]. The graphs consist evaluation technique is employed to update the query
of activities (nodes), and links (edges) between them, result.
that detail the execution order of activities. Each
activity is represented by a pair of nodes, the first III SYSTEM OVERVIEW
standing as the activity’s activation point and the We give here a brief overview of the main
second as its completion point. Activities may be components and their interaction. Figure 1 depicts the
either atomic, or compound. In the latter case their system architecture.
possible internal structures (called implementations) Store Model[6]: The abstract model of the on-line
are also detailed as DAGs, leading to the nested store application and its cWeight information are
structure. A compound activity may have different stored in the ShopIT database.
possible implementations, corresponding to different
user choices, link traversals, variable values, etc. The first component, namely the application
These are captured by logical formulas (over the user abstract model, was manually configured. Many
choices, variable values, etc.) that guard each of the Web-based applications are specified in declarative
possible implementations. A Web-based application languages and then an automated extraction of their
may be recursive, where an (indirect) implementation abstract model structure is possible. The products
of some activity a contains another occurrence of a. information, including compatibility relation in-
between products, as well as additional parameters
Navigation Flow: A navigation flow[6] (in a given such as products cost, discount deals, shipment time
application) corresponds to concrete choices of etc. were automatically retrieved via a standard Web
implementations for compound activities. For interface. The cWeight function was automatically
instance, a possible navigation flow in our computer derived to reflect this data.
store is one where the user first reviews the possible
deals, then chooses to purchase an Intel Motherboard,
subsequently cancels her choice, buys a discount
coupon and selects a CPU by HP, etc. Note that the
number of possible navigation flows may be
extensively large even for relatively small-scaled
applications.
Ranking: The rank[6] of navigation flows is derived
using two functions, namely, cWeight and fWeight.
Function cWeight assigns a weight to each single
(implementation) choice within a flow, depending on
the course of the flow thus far and the objective that
the user wishes to optimize, e.g., monetary cost or
likelihood. Function fWeight aggregates the per-
choice weights in a single score for the entire flow.
Top-k query results: The users’ search criteria[6] are Fig 1: System Architecture
modeled by queries. These use navigation patterns,
an adaptation of the tree patterns, found in existing Query Engine: The query engine[6] is composed of
query languages for XML, to nested application two components. The first is the Top-k queries
DAGs [1]. Our top-k query evaluation algorithm gets evaluator that receives, as input, from the user, her
as input the schematic representation of the search criteria and chosen ranking metric, and
application, the user query and the chosen ranking computes the initial suggestion of top-k qualifying
metric, and efficiently retrieves the qualifying navigation paths. ShopIT supplies a Graphical User
navigation flows with the highest rank. The algorithm Interface that allows users to specify their criteria for
operates in two steps. First, it generates a refined search. The specified criteria are compiled into a
version of the original application representation, navigation pattern, which in turn is evaluated over the
describing only flows that are relevant to the user Web Application model.
request. Then it greedily analyzes the refined
representation to obtain the best-ranked flows. The The second component is the adaptive
choices made by the user throughout the navigation recommendation engine that is continuously
are modeled as additional constraints/relaxations to informed about the user actual navigation choices (or
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3. Venkata Ramana Kumari.Ch, B. Sowjanya Rani / International Journal of Engineering Research
and Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 4, July-August 2012, pp.534-538
changes to her search criteria and ranking choice) and then we terminate. Otherwise, every node appearing
adapts the offered top-k suggestions accordingly. We in e, along with its preceding sub flow defines an
have designed the query engine so that it is accessible equivalence class, used as entry at F Table. The sub-
through an API that allows the placement of user flow rooted at the node is then inserted into the table
queries and preferences, and the retrieval of the at that entry, if it does not appear there already. Last,
corresponding recommendations. This general API all EX-flows that were put by Handle Partial due to a
can be used to incorporate ShopIT within a given node participating in e, are returned to Frontier.
website.
The ShopIT virtual store: Users interact with a
virtual store[6] that wraps the original store. User
actions are passed, through the API, to the ShopIT
engine and to the (original) store application. The
obtained recommendations are then presented to the
user alongside with the resulting store screens. Each
recommendation consists of a sequence of proposed
actions, such as “click on button X”, “choose option
Y at box Z”, etc., and is accompanied by its
corresponding weight (e.g. total price, likelihood,
etc.).
IV OPTIMAL TOP-K ALGORITHM
TOP-K Algorithm [2, 5]: we define an EX-
flows table, F Table, (compactly) maintaining the
top-k (sub) flows for each equivalence class. It has
rows corresponding to equivalence classes, and
columns ranging from 1 to k. Each entry contains a
pointer to the corresponding sub-flow. In turn, every
implementation of a compound activity node in this HandlePartial: Handle Partial is given a partial flow
sub-flow is not given explicitly, but rather as a e and considers all possible expansions e′ of e. To
pointer to another entry in F Table, and so on. This that end, we assume the existence of an All Exps
guarantees that the size of each flow representation is function that allows to retrieve, given a partial flow e,
bounded by the table size, avoiding the blow-up of all of its expansions (i.e. all e′ s.t. e → e′ ), along with
EX-flow sizes. In what follows, every EX-flow is their weights. The algorithm first retrieves the next-
represented via a single pointer to an entry at F Table. to-be- expanded node v of e, and looks up its
The algorithm then operates in two steps. First, it equivalence class in F Table. If no entry is found, it
calls a subroutine FindFlows which computes a means that we haven't encountered yet an equivalent
compact representation of the top-k EX-flows within node during the computation. We thus create a new
F Table, and then it calls Enumerate Flows that uses row in F Table for this equivalence class. Entries in
the table to explicitly enumerate the EX-flows from this row will be filled later, when corresponding full
this compact representation. We next explain the flows are found. Then, we obtain all expansions of e,
operation of these two subroutines. and for each such expansion we compute its fWeight
Find Flows: The Find Flows procedure maintains value, and insert it to the Frontier queue for
two priority queues Frontier and Out of (partial) EX- processing in the following iterations. Otherwise, if
flows, ordered by fWeight. At each step, Frontier the appropriate row already exists in the table, we
contains all flows that still need to be examined. consider the partial EX-flows that appear in this row
Upon termination, Out will contain the top-k flows. but were not yet considered for expanding e. If no
Initially, Out is empty and Frontier contains a single such EX-flow exists, (although the table entry exists),
partial EX-flow, containing only the BP root. At each it means that e was previously reached when
step, we pop the highest weighted flow e from expanding some other node v′ (which appears in e as
Frontier. If e is a full (partial) flow, the algorithm well). We may compute the next best EX-flow
invokes Handle Full (Handle Partial) to handle it. without further expanding e. Thus, we put e on hold.
It will be released upon finding a full flow originating
HandleFull: First, the given full EX-flow e is in v′. If an unused EX-flow exists, we take the
inserted into Out. If Out already contains k flows, highest ranked such EX-flow and “attach" it to v, that
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4. Venkata Ramana Kumari.Ch, B. Sowjanya Rani / International Journal of Engineering Research
and Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 4, July-August 2012, pp.534-538
is, we make v point to this flow. We now compute distributions with average value of 0.5 and varying
the weight of the obtained EX-flow and add it to standard deviation of 0.2, 0.1, and 0 (the latter
Frontier. corresponding to all-equal cWeight values). WC
always fills in all entries of the FTable, thus is not
sensitive to the cWeight distribution, and we show
only one curve for it.
Figure 1(b) examines the execution times of
WC and TOP-K for a growing number k of requested
results (for the same distributions of cWeights as
above). The number of equivalence classes here is
200K and the history bound is 5. We can see that the
running time increases only moderately as k grows,
with TOP-K steadily showing significantly better
performance than WC.
V EXPERIMENTAL STUDY
We present an experimental study of our
algorithm based on synthetic and real-life data. The
study evaluates the performance of the algorithm in
practice relative to the worst-case bounds implied by
our analysis, examining cases where optimality is
guaranteed as well as cases where it is not.
Note that TOP-K gradually fills in F Table,
and halts once it discovered the top-k flows. We
implemented a variant of TOP-K, termed WC (for
worst-case), that fills in all entries of F Table before
terminating, and compared the performance of TOP- Figure 1(c) examines the e®ect of the
K to WC that provides a comparison to [8]. A monotonicity strength of the weight function, on
comparison of TOP-K to WC demonstrates the TOP-K's execution time. We fix k, the number of
significant performance gains achieved by our new equivalence classes, and the history bound (to 100,
algorithm. 40K, and 5, resp.), and vary the percentage of neutral
weights, with the non-neutral weights uniformly
A representative sample of the experimental distributed. At the left-most end, there are no neutral
results is presented below. Figure 1(a) examines the weights and TOP-K is guaranteed to be optimal; at
execution times (in seconds) of TOP-K and WC for the right-most (very unlikely) case all weights are
increasing number (in thou- sands) of equivalence neutral, and TOP-K and WC exhibit the same
classes. (The scale for the time axis in all graphs is execution times (as the flows table must be fully
logarithmic). The number k of requested results here filled). We see that the performance of TOP-K is
is 100. (We will consider varying k values below). significantly superior even when the conditions for
The figure shows the performance of TOP-K for optimality do not necessarily hold. In particular, in all
cWeight values in the range [0, 1] with different realistic scenarios where less than 90% of the weights
distributions. This includes uniform and normal
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5. Venkata Ramana Kumari.Ch, B. Sowjanya Rani / International Journal of Engineering Research
and Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 4, July-August 2012, pp.534-538
are neutral, TOP-K improves over WC by more than line shoppers by suggesting the most effective
75%. navigation paths for their specified criteria and
preferences. The suggestions are continually adapted
to choices/decisions taken by the users while
navigating. ShopIT is based on a set of novel,
adaptive, provably optimal algorithms for TOP-K
query evaluation in the context of weighted BPs
(business process). We analyzed different classes of
weight functions and their implications on the
complexity of query evaluation, and have given, for
the first time, a provably optimal algorithm for
identifying the top-k EX-flows of BPs [5]. We
showed that our algorithm outperforms by an order of
magnitude.
VII REFERENCES
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Fig. 1(d) depicts results for 15 representative
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such subsets, involving increasing counts of
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