A Case-Based Perspective on Social Web Search
Presenters: Amit Balode, Anindya Lahiri
Summary
Search engines are the primary source for people to access online information. We often search information that has been searched before by our peers. Thus we waste time by searching the same thing again. The currently available search engines do not allow saving past search knowledge nor do they allow sharing the search experiences with others. Sharing search knowledge and thus make searching more efficient can achieved by making search a social activity.
The paper introduces HeyStaks, a web search utility tool that adds collaboration features and a host of social networking functions to the search engine like Google. The tool stores knowledge of past searches as Case-Bases which can be shared among peers.
HeyStaks allows users to organize and save their search experiences and allows users to share them easily with friends and colleagues. The tools thus forms case bases of such search experiences. It also facilitates collaboration by forming case-bases of previous search experiences of like-minded people.
The paper, “A Case-Based Perspective on Social Web Search” further discusses about the beta implementation of the toolbar and its architecture and properties. The properties of the tool, HeyStaks are:
- Compatible with prominent search engines like Google
- Allows users to group searches into staks
- Each stak is case base of a search experience
- Gives user the option to share a stak or use already created search stak
- The tool recommends top few searches as promotional, i.e. these are generated by the tool
- Google’s normal search results are appended below the promotional recommendations
- Shows additional search links at the top of all the search links which do not qualify as promotional links
Strengths/Conclusions:
- Saves time on searching as most are about re-searching information
- Allows collaborative/ case-based Search
- Better way to organize and share their search experiences
- Provides choice between search engine results as well as recommended results from the tool
Weakness/Questions:
- How many of them are returning users?
- How frequently is the stak updated?
- Is the stak getting manipulated by hackers?
- How might case bases be recommended?
- Given that the search case bases are much noisier that expert-created case bases, how should this influence retrieval, reuse, and maintenance?
- As case bases evolve there may be opportunities to merge related case bases, or case bases may start to diverge as different contributors use them in different ways. How might these opportunities to merge or split case bases be recognized and handled?
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