The Next Generation of Shopbots

2011 ◽  
pp. 19-36 ◽  
Author(s):  
Maria Fasli
Keyword(s):  
Decision Making ◽  
Web Services ◽  
Semantic Web ◽  
Online Shopping ◽  
Vast Number ◽  
High Expectations ◽  
Profound Impact ◽  
Comparison Shopping ◽  
Shopping Experience ◽  
Immense Potential

The huge growth of e-commerce has had a profound impact on users who can now choose from a vast number of options online. Inevitably, as the number of choices has increased, so has the need for tools to help users organize, manage and utilize information on these for better decision-making. Comparison shopping agents or shopbots can help users decide what to buy and enhance their online shopping experience. However, despite the high expectations, the immense potential of shopbots has not been fully realized. In this chapter, the author identifies the limitations and drawbacks of current shopbots, in particular, with regard to the underlying technology for building such systems. She then discusses how these technical limitations can be overcome by making use of the Semantic Web and Web Services. She also considers how shopbots can truly serve the user by providing personalized, impartial and flexible services.

India Goes Digital..Smartphone is the New Shopping Destination

2018 ◽  
Vol 6 (8) ◽  
pp. 289
Author(s):  
Shankar Chaudhary
Keyword(s):  
Online Shopping ◽  
Mobile Apps ◽  
Smart Phone ◽  
Mobile Commerce ◽  
Mobile App ◽  
Smart Phones ◽  
The Internet ◽  
The World ◽  
Shopping Experience ◽  
User Friendly

Despite being in nascent stage m-commerce is gaining momentum in India. The explosive growth of smart-phone users has made India much loved business destination for whole world. Indian internet user is becoming the second largest in the world next to China surpassing US, which throws open plenty of e-commerce opportunities, not only for Indian players, offshore players as well. Mobile commerce is likely to overtake e-commerce in the next few years, spurred by the continued uptrend in online shopping and increasing use of mobile apps.The optimism comes from the fact that people accessing the Internet through their mobiles had jumped 33 per cent in 2014 to 173 million and is expected to grow 21 per cent year-on-year till 2019 to touch 457 million. e-Commerce brands are eyeing on the mobile app segment by developing user-friendly and secure mobile apps offering a risk-free and easy shopping experience to its users. Budget 4G smart phones coupled with affordable plans, can very well drive 4G growth in India.

Design, Development and Comparison of Heuristic Driven Algorithms Based on the Crossed Domain Products’ Reviews for User’s Summarization

2020 ◽  
Vol 13 (5) ◽  
pp. 884-892
Author(s):  
Sartaj Ahmad ◽  
Ashutosh Gupta ◽  
Neeraj Kumar Gupta
Keyword(s):  
Decision Making ◽  
Online Shopping ◽  
Recent Time ◽  
Design Development ◽  
Different Types ◽  
Feature Based ◽  
Use Of Internet ◽  
Day By Day ◽  
Better Than

Background: In recent time, people love online shopping but before any shopping feedbacks or reviews always required. These feedbacks help customers in decision making for buying any product or availing any service. In the country like India this trend of online shopping is increasing very rapidly because awareness and the use of internet which is increasing day by day. As result numbers of customers and their feedbacks are also increasing. It is creating a problem that how to read all reviews manually. So there should be some computerized mechanism that provides customers a summary without spending time in reading feedbacks. Besides big number of reviews another problem is that reviews are not structured. Objective: In this paper, we try to design, implement and compare two algorithms with manual approach for the crossed domain Product’s reviews. Methods: Lexicon based model is used and different types of reviews are tested and analyzed to check the performance of these algorithms. Results: Algorithm based on opinions and feature based opinions are designed, implemented, applied and compared with the manual results and it is found that algorithm # 2 is performing better than algorithm # 1 and near to manual results. Conclusion: Algorithm # 2 is found better on the different product’s reviews and still to be applied on other product’s reviews to enhance its scope. Finally, it will be helpful to automate existing manual process.

A Decision-Making Framework for Inventory Positioning in an Omnichannel Business Environment

2019 ◽  
Vol 12 (1) ◽  
pp. 81-94 ◽  
Author(s):  
Albert Wee Kwan Tan ◽  
David Gligor
Keyword(s):  
Decision Making ◽  
Business Model ◽  
Business Environment ◽  
Shopping Experience ◽  
Decision Making Framework ◽  
Customer Orders

Omnichannel is an evolving business model that has been gaining increased popularity among retailers. This business model allows firms to use a variety of channels to interact with their customers and fulfill their orders. Customers can order online and pick up later in the store, or they can choose to have the products delivered from a nearby store. Due to the complexity of fulfilling customer orders via omnichannel models, positioning inventory is a key challenge in supporting this type of business model. This article presents a framework for assisting companies in deciding under what condition to centralize or decentralize their inventory to fulfill customer orders without disrupting the shopping experience.

PROCESS MODEL ONTOLOGY-BASED MATCHMAKING OF SEMANTIC WEB SERVICES

2011 ◽  
Vol 20 (04) ◽  
pp. 357-370 ◽  
Author(s):  
D. PAULRAJ ◽  
S. SWAMYNATHAN ◽  
M. MADHAIYAN
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Web Service ◽  
Process Model ◽  
Service Discovery ◽  
Service Oriented Architecture ◽  
Semantic Web Services ◽  
Functional Part ◽  
Service Oriented ◽  
Concise Description

One of the key challenges of the Service Oriented Architecture is the discovery of relevant services for a given task. In Semantic Web Services, service discovery is generally achieved by using the service profile ontology of OWL-S. Profile of a service is a derived, concise description and not a functional part of the semantic web service. There is no schema present in the service profile to describe the input, output (IO), and the IOs in the service profile are not always annotated with ontology concepts, whereas the process model has such a schema to describe the IOs which are always annotated with ontology concepts. In this paper, we propose a complementary sophisticated matchmaking approach which uses the concrete process model ontology of OWL-S instead of the concise service profile ontology. Empirical analysis shows that high precision and recall can be achieved by using the process model-based service discovery.

Sign in / Sign up

Export Citation Format

Share Document