computational challenges in e-commerce by joan feigenbaum, david c.parkes, and david m.pennock...
TRANSCRIPT
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Computational Challenges in E-Commerce
By Joan Feigenbaum, David C.Parkes, and David M.Pennock
Presented by Wu Jingyuan
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Contents
Overview of E-Commerce
Resource Allocation
Knowledge integration
Peer Production and Interaction
Security and Privacy
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What is E-Commerce?
Electronic commerce: commonly known as e-commerce or ecommerce,
consists of the buying and selling of products or services over electronic
systems such as the Internet and other computer networks.
In this article, we focused on Internet-based commerce.
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Four Areas of Computational Challenges
Individuals & organizations that use computers are autonomous. Generally, they
will act to maximize their self-interest which is not considered in traditional algorithm
design.
Incentives plays a crucial role in the four areas of computation:
Resource Allocation, Knowledge Integration, Peer Production and Interaction, and
Security and Privacy .
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Resource Allocation
Resource Allocation is a fundamental process that used to assign the
available resources in an economic way.
Participants declare their perceived value for the resource.
Market computes the best allocation and the prices that participants should
pay.
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Auction
Auction is a decentralized prescription for resource allocation.
Classical auctions emphasize simple rules for setting allocations and prices
manually.
Combinatorial Auctions allow bidders to express values for bundles of goods.
Sometimes it’s NP-hard. For example, they are used to source truckload-
transportation logics for Procter & Gamble, Walmart, and Taget.
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Advertising
Advertising is a business based on allocating attention.
Historically, advertising sales featured straightforward allocation rules and
manual negotiations.
Now, More aspects of advertising are being automated.
-Google & Yahoo!
-Edelman et al. and Varian model
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Knowledge Integration
In general, knowledge integration is the eliciting and aggregation of
information from diverse and frequently self-interested sources.
“price discovery” - a side effect of market-based resource allocation.
- “Prediction Market”
- Rating and reputation systems
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Prediction market
Liquidity: -Adjust prices dynamically. -Ensure a bound on the worst case loss.
Expressiveness: -Severe computational cost. -Compromise with computational complexity.
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Rating and Reputation System
Gathering Subjective opinions
on a variety of things.
No fundamental truths.
Provide considerable value.
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Peer Production and Interaction Peer production refers to large-scale collaboration that is not based on price signals. -Salient examples: Wiki, Linux. -Social production: Youtube, Facebook.
Motivations: pleasure, communications or other regarding preferences.
Challenges: -observe behaviors with a view to learning preferences.. -modulate environment through appropriate constraints and affordances.
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Peer to Peer
Early protocols failed to provide appropriate incentives for the uploading of files. -Gnutella suffered from a large amount of free-riding.
The BitTorrent protocol. -Limit users’ download rate according to upload history -Inefficient market.
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Trust Metrics
EigenTrust algorithm
-Sybil attack
Improved algorithm
-Shortest path
Challenges:
-Find a satisfactory definition of informativeness.
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Security and Privacy
An economic trade-off between privacy intrusion and satisfactory interactions. -Individuals -Organizations
Unwanted communication. -email spam -Link spam, shilling and click fraud
Copyright enforcement
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Summary
Self-interest plays a crucial role in the procedures of e-commerce.
The design of Internet protocols and services have often been guided by
technology rather than economics.
Economic and social science will drive Internet protocols and services into
the future.