A Brand New

Socialized Service Search

Ecosystem

The amount of web pages on the internet is growing rapidly. We are in desperate needs of information to keep up with the changing world. In the meanwhile, we are enjoying the service provided by advanced technology as well as human labor. We offer service for others and served by them. Computing technology is making the service more and more available.

 

Here is the story. We use search engine everyday, such as Baidu and Google. We query for information and get the ranked web pages. We query like Barack Obama, best selling books this month and which is the most popular programming language? Sometimes we have some queries, but cannot get satisfied results from the traditional search engine, such as get me a cab, fix my computer, and i need a house cleaner right now. From these queries, what we want to get is specific service or some people can providing specific service. In reality, people with skills like taxi driver, computer fixing and house cleaning just around us. What if we connect the service requesters and qualified service completers?

 

The Power of Mobile Crowd

 

As one of the most successful forms of using wisdom of crowd, crowdsourcing has been widely used for many human intrinsic tasks, such as, image labeling, natural language under- standing, market predictions, and opinion mining. Meanwhile, with the advances in pervasive technology, mobile devices, such as mobile phones and tablets, have become extremely popular, which makes mobile computing a popularity.

 

Crowdsourcing is a very efficient way in helping people to complete complex projects from grassroots. Unlike traditional methods, it is human workers who play the key role of task completion. Popularity of mobile devices makes the Location Based Services (LBS) a compelling paradigm that information technology can provide for us as services. Users carrying with mobile devices can travel places to places to collect various multimedia data, accomplish service tasks and get together playing. Mobile crowd service has the potential to acquire massive data from spatial palaces and address large-scale societal problems. This economic and efficient architecture has gained extensive attentions both in researches and industries.

 

Location based Service Engine

 

The invention of internet is amazing and the technology of search engine is marvelous. The internet makes information connected in the world, which makes knowledge accessible for everyone. Search engine, such as Google and Baidu, provides us an efficient way of accessing and obtaining information in an easy way. Besides the information retrieval technology, recommendation system is emerging to help people get accurate and instant information. However, the needs of human never stop, and so do the technology in computer science.

 

The most exciting practices of location based service, such as Airbnb and Uber, give us a new vision that information technology can provide us, the power of grassroots and essential of offline services. We need not only online services but also offline services. We read news on the internet, watch television on the internet, even learn on the internet. Internet provides us online and virtual services in its best way. But we, as human being, need offline activities and services, too. We go the theaters, rent cars, play basketball and eat in a restaurant. The technology of computer science should and can provide us enjoy of offline services.

 

The Long Tail Theory

 

As we have mentioned, Airbnb provides us hotels, Uber provides us cars, Yelp provides us restaurants. However, some special-interest and small-group services need being satisfied. What if I need fixing my computer, fetching my delivery and want to gather someone to play basketball. That is the long- tail theory of services, which encourages the platform to be general. Besides eating, clothing, housing and travelling, we have more long-tailed needs to be satisfied. The long tail theory pushes us shifting away from a focus on a relative small number of ”hits” (mainstream products and markets) at the head od the demand curve and toward a huge number of niches in the tail.

 

HelPal: A General Service Engine for Mobile Crowds

 

The power of crowdsourcing and mobile computing makes it possible to implement a new service mode: mobile crowd service. The users carrying with mobile devices can travel places to places to collect various multimedia data, accomplish service tasks and get together playing. Mobile crowd service is likely to become more popular than the general crowdsourcing since it harnesses the power of mobile people out in the web to do spatial tasks that are hard for individual users or computers to do alone.

 

However, to implement such a mobile crowd service plat- form, service engine as we call, it is not easy. Rather than the useful information from web pages in search engine, it is the mobile users who make contributions. Service engine harvests the flexible human labor from places to accomplish various tasks. Search engine collects the world wide webs while service engine aggregates the massive spatial human labors.

 

We design and implement HelPal, a general location based service engine for mobile crowds to provide instant and intelligent service.

 

• General: Any crowd based services can be applied in this platform, especially for the long-tail users;

• Mobile: It takes the advantages of mobile devices and it is a offline location based service;

• Service: It provides available and flexible service labor for users rather than cyber information;

• Instant: It guarantees the time-efficiency of service by indexing and other key techniques;

• Intelligent: We match the request of service from users to the qualified service provider i.e. turks accurately combining query matching and task recommendation techniques.

 

We design a general service engine for mobile crowds with contributions of system architecture, key techniques, perfor- mance evaluation and prototype implementation. We aim to make HelPal the next information engine from search engine, Service Engine.

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A DEMO  video can be found at Youtube.

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A PDF can be found at Google Docs.

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The 2-pages Proposal can be found at Google Docs.