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GiveALink is a social bookmarking site where people can donate their bookmarks to the Web community and to science. As an ongoing academic research project, our goal is to analyze bookmark files to build new Web mining techniques including new ways to search, recommend, personalize, and visualize the Web.

We do not use page content nor links from submitted Web pages. Instead we use the hierarchical structure in individual bookmark files, when present, and collaborative filtering across users to measure semantic similarity of pages. Simply put, if many users bookmark two pages and put them in the same folder, the pages are probably related somehow; if they don’t, they’re probably less so. We then use this similarity to provide recommendations and a search engine.

Registered users may view and maintain their personal bookmark files online, as well as get personalized search results and recommendations based on their submitted bookmarks.

Why donate bookmarks?

People like types of books, types of music, and types of clothes—they also like types of websites! We collect information about what sites people bookmark and how people organize their bookmarks because we want to measure the semantic relationship between websites. By donating your bookmarks, you let GiveALink analyze your preferences along with those of many other people. We will mine the resulting collection for interesting insights and use the information to develop novel applications. We will also share bookmark data (see question on privacy) with the Web research community, hoping to foster the development of many novel Web mining techniques and applications to search, recommendation, navigation, personalization and visualization of the Web.

My bookmarks are not organized, should I donate?

Yes, please donate your bookmarks no matter how untidy or strange they are! We are interested in the structure of the file and our algorithms are able to extract more similarity information from bookmarks that are organized in folders. But we really prefer that you donate your bookmark files unedited, the way you use them. In addition, we would like to grow our bookmark collection quickly because the more donations we get, the better our systems will be. Please challenge our algorithms and donate all of your bookmark files, regardless of what they look like.

What browsers are supported?

We can currently accept bookmark donations from people using Internet Explorer (IE), Netscape, Mozilla, Firefox, Opera, and Safari. In the future we might extend this list. Note that in IE, bookmarks are called favorites. Please donate the bookmarks from the browser used for donation. For example, do not use Firefox to donate Safari bookmarks. There are two reasons for this: (1) we detect your browser and use this information to parse your bookmarks; and (2) you can donate multiple sets of bookmarks if you use multiple browsers for different activities—we will store multiple sets of bookmarks from different browsers under your profile.

OK, what do you want to do with the bookmarks?

 We are developing a number of exciting new applications using the semantic data we gather from your donated bookmarks. Some are already available online:

• Interactive Graph of Sites with High Generality - We identify the most central sites on the Web, i.e. the sites with highest generality, and visualize them using the interactive package prefuse.
• Recommendation System - Type in the address of a site that you like and we will suggest similar bookmarks. The similar bookmarks are identified from the collections of bookmarks submitted to our site.
• Search Engine - Enter words describing the subject you are searching for and we will suggest relevant sites! This system looks a lot like Google and Yahoo. However, instead of crawling the Web to find pages that contain the search words, we match the search words against the titles and descriptions contained in our bookmark collection.

 Here are some other ideas we are working on:

• Recommendation System Based on User Profiles - This system will recommend sites based on all the bookmarks that you have submitted.
• Personalized Search - Personalized search will be based on what you and other people with similar interests think are great websites in relation to your queries or sample sites.
• Data Mining - We will explore new ways to distill knowledge from the huge collection of pages making up the Web. We will try to identify trends, time sequences, and popular sites based on semantic links between pages mined from bookmarks, rather than hyperlinks from page content. We will also be able to cluster both people and websites based on their similar interests and meanings, and to classify pages into personalized taxonomies.

What is the "Top Ten Bookmarks" list on the GiveALink home page?

This list shows the URLs in the GiveALink database that got highest prestige scores. Prestige is one of our global ranking measures, which is similar to PageRank. It identifies Web pages that are most central to our database, that a lot of users donate and that have high average similarity to other bookmarked Web pages. Read more about our ranking measures here.

How is GiveALink different from other bookmark sharing sites?

There are several great websites that allow people to submit their bookmarks and provide very useful services such as sharing, search, and full-text search. These include Simpy, Delicious, Furl, and Backflip. GiveALink is not competing with these sites, on the contrary we hope to collaborate with them. GiveALink is different in that we are a non-commercial research project. As such, we will make both our data and our algorithms openly available to the Web community (see questions on privacy). We will also focus our energy on the development of novel Web mining techniques and applications that are not already available elsewhere. For example, we are working on a novel semantic similarity measure that exploits the hierarchical structure of bookmark files.

How does the URL search work?

At GiveALink, we collect bookmark files from people willing to donate them. These bookmark files reveal patterns and related sites that are identified using a novel semantic similarity measure. Our measure exploits the hierarchical structure of bookmark files. For example, if many users put two URLs in the same folder in their bookmark files, then the two URLs are probably very similar. However if the two URLs are always in different folders, then they are probably not related.

How does the keyword search work? Is it different from Google and Yahoo?

Our keyword search looks a lot like Google and Yahoo: you can enter words describing the subject you are searching for and we will suggest relevant sites! However, instead of crawling the Web to find pages containing the search words, we match search words against titles and descriptions in our bookmark collection. We only recommend sites from our bookmark collection—sites that a human has bookmarked as relevant to what you are looking for!

What is "Surprise Me"? Is it different from "General" search?

Sometimes sites can be related to each other, but not in an obvious way. For example, in the Simpsons, Bart and Moe are not directly related to each other, but they are similar in a way because they both spend a lot of time with Homer. Our "Suggest Novel URLs" attempts to identify sites with connections that may not be obvious.

"Surprise Me" keyword search is very similar to "Surprise Me" URL search: it suggests sites that are relevant to your search words but in a way that is unexpected and not obvious. The difference is that the first expects you to enter search words while the latter expects you to enter a valid URL.

What are bookmark similarity, novelty, and prestige?

You can sort your search results using three measures: bookmark similarity, novelty, and prestige. You can also sort by the product of any combination of the measures. For example, if you select novelty and prestige, the top result will be one with high (novelty * prestige) rank, i.e. a site that has high novelty and high prestige.

• Similarity - Bookmark similarity is a novel semantic similarity measure that exploits the hierarchical structure of bookmark files. We use Lin’s measure to calculate the similarity of two URLs in the bookmark collection of one user. To obtain a similarity value for one pair of URLs, we sum up the similarity that our users report.
• Novelty - The novelty of a recommended site is the ratio of indirect similarity over direct similarity to the search URL. For example, in the Simpsons, Bart and Moe are not directly related to each other, but they are similar because they both spend time with Homer. Thus if you are searching with keyword "Moe", the recommendation "Bart" will have high novelty because the two have high indirect similarity and low direct similarity.
• Prestige - Prestige is a global ranking measure that is independant of the query URL and keywords. It generates scores for the URLs in the GiveALink database similar to the way PageRank does. In simple terms, it identifies Web pages that are central to out database, that a lot of users donated, and that have high average similarity to other bookmarked Web pages. In mathematical language, prestige orders URLs according to their corresponding values in the principle eigenvector of the similarity matrix.

publisher-author

Trustees of Indiana University

License

Free

Platform

All Platforms

Money Back

n/a

See too

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