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LikeMe, a social recommendation site similar to Yelp.com lets users rate and review local businesses, attractions, restaurants, and clubs. After you join the service, you can upload info about yourself, your favorite places, and your favorite things to do in order to kick start the service's personalized social recommendation engine.

Now the app joins a handful of others (really, just a handful) on the new Palm Pre. But before you go and download this one, there's something you need to consider about LikeMe: their reviews may be compromised.

Today from AdaptiveBlue there comes a new version of the semantic browser extension Glue (previous coverage) which allows you to create a browser-based social network around the things you and your friends find online. This latest release, four months in the making, finally makes Glue compatible with Internet Explorer - a move which Glue's creators hope will allow them to tap into a wider, more mainstream audience.

Ohpan, the scrolling news ticker web site we covered a few months prior, recently released an iPhone application which uses their same recommendation engine technology to deliver you the best content. As with their main web site, the iPhone app lets you rate the content you see to allow Ohpan to learn your preferences. However, the app also takes advantage of the iPhone platform to offer localized content as well as some other unique features.

Given how much user activity goes on every day on Facebook, the company has to be working on some kinds of recommendation technologies. Charming invisible robots that say, "If you like this, then you'll like that." Full-time Facebook watcher Nick O'Neil thought he spotted one in the wild this morning, but his readers make a convincing case that he was wrong this time.

The feature O'Neil wrote about appears to be nothing more than the latest FriendFeed rip-off: truncating repetitive activities. (Ex-Googler Paul Buchheit's FriendFeed is like a Facebook R&D lab without stock options.) Whether Facebook is doing more than that publicly or not, you know they have to be working on recommendation behind closed doors.

A website (whether a URL, domain, brand, etc.) is a place where the owner, individual visitor, and broader web community come together for a shared purpose. At first, the web adopted a feudal model of "place": owners held all the authority; they depended on the serfs (visitors) to extract value but allowed them no participation in governance, content, or presentation. That model has largely disintegrated.

A new online community site called Lunch.com has just launched into private beta here at the Web 2.0 Expo in San Francisco. The site, essentially a recommendation network, aims to bring the sort of casual conversations you would have with friends over lunch to the online arena. Using a proprietary "Similarity Network Engine," Lunch calculates what you have in common with other site members so you can share recommendations with those who have your same interests and perspectives.

In this latest installment in our series on recommendation engines, we look at ChoiceStream - a recommendations vendor which counts Overstock, Borders and AT&T among its high profile clients. ChoiceStream has recently turned its attention to using recommendations in online advertising, and in this post we look at how the company is doing this. The ChoiceStream advertising product aims to generate personalized banner ads for each consumer, using data on shopping and buying patterns that it collects from the advertiser's website. The company claims that this technology improves click-thru rates, conversion rates and average order size.

The personalized news service Veritocracy dropped its beta badge today, opening its doors for everyone to register and try their hand at being a story editor. Veritocracy (or Veri) compares itself with Pandora, but for news instead of music. You search for broad topics (think politics or internet) and the site presents you story clusters which you can then vote up, vote down, or even submit your own content. Veri's motto: "Better information finds you."

Loomia is a content recommendations service, used on sites such as the Wall Street Journal and PC World. We've profiled Loomia's Facebook app before, which tracks what you and your Facebook friends are reading on Loomia-supported sites and then shows you what content is most popular among your social circle. Loomia has recently started to focus on revenue-driving recommendations for its media clients, as well as getting more active in the video industry. In this post we take a look at what Loomia is focusing on in 2009, which is an indicator of what media websites must do to ramp up this year.

In this latest installment in our series on recommendation engines, we look at MyBuys - a company purely focused on providing recommendations services to retail websites. We've noted in previous posts in this series that each recommendations vendor has a different approach. What distinguishes MyBuys is that it takes a services approach and is not based on a single algorithm. We spoke to Paul Rosenblum, VP Products & Strategy at MyBuys, who told us that most companies in the recommendations market have a "pet algorithm". However MyBuys, according to Rosenblum, uses a variety of algorithms for different contexts and different kinds of retailers. "Fundamentally", Rosenblum told ReadWriteWeb, "we don't actually have a product [...] we have a service".