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Social Search Engine

Social Search Engine. Using trusted metadata to improve the relevance of search results. Social community. Existing Search engines. +. Examples: Engineers Doctors Artists Politicians. Examples: Yahoo Search MSN Search Google Search AltaVista Search. Social Searching.

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Social Search Engine

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  1. Social Search Engine Using trusted metadata to improve the relevance of search results

  2. Social community Existing Search engines + • Examples: • Engineers • Doctors • Artists • Politicians • Examples: • Yahoo Search • MSN Search • Google Search • AltaVista Search Social Searching

  3. What is social networking ? • Man is a social being. • He relies highly on the inputs provided by people he trusts. • Social networking refers to a category of Internet applications to help connect friends, business partners, or other individuals together using a variety of tools. • Searching techniques currently employ different algorithms to index and to display pages in a particular order.

  4. Search Techniques Types of search Naïve Search User searches for “India", and the page containing “India" the most number of times is chosen by search engine.

  5. Search Techniques Page Rank and inferred quality User searches for “India", and the page with the most incoming links is chosen by search engine.

  6. What are the drawbacks ? • The results which get priority in ordering are not always the best links. • Search engines do not differentiate between the good pages and the bad pages. • Rankings of a webpage can be influenced using techniques such as Google bombing and Spamdexing. • These ordering techniques mostly do not rely on user feedback.

  7. The Solution Social networks to determine subjective quality 1 2 3

  8. Then, how can we improve ? • Build a community and ask its members to give ratings for web pages that they visit, when they search using a specific keyword. • As you trust your community better than the actual search engine results, you normally tend to visit the links recommended by your community. • The entire concept is based on TRUST! • The bigger the community, the better your search results.

  9. So, what do we do ? • Use an already available API to fetch web results. • Re-order these results to employ user feedback and rating. • For this, we maintain a central repository of a user’s buddies or friends. • Reorder the search results based on community feedback.

  10. An Illustration • Pooja enters a search query “news”

  11. What does she get ? • She gets back a lot of results, but how can she know which link is more relevant to what she is looking for?

  12. The SpaK solution • Pooja trusts her friend Siddu and FOX news is rated good by Siddu.

  13. That was in case of a good website! What if the website is a malicious website that inserts some spy-ware or ad-ware into your system ?

  14. Bad Bad websites! • software vulnerabilities are increasingly exploited by malicious websites

  15. The community’s opinion as a whole! • Karthik has already been fooled once.. So he has rated the website as bad!

  16. What happens next ? • Now Pooja knows that the website is a malicious website and she must proceed (if at all!) with caution. • Though Siddu rated the website as good, there were two other people who rated the website as bad! • Social Networks tend to increase your security blanket, though it may not be an alternative to a good antispyware software!

  17. SpaKSEARCH • That’s our project! • Our aim is to build a community of people and then, employ member feedback to enhance the search results.. • We fondly call it..

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