Although there are endless supply of themes and plugins on WordPress, but if you want to run WordPress not only for your blog, but as a job board, here we’ve gathered up few themes and plugins for you to start out your WordPress powered job board.

Themes:

JobPress – A very job board-specific theme that allows users to set up their own job boards. You also can accept job listing fee via PayPal.

Templatic Job Board – You can set the option whether to allow free job listings or to have paid listing on the theme settings. Also, this theme comes with 7 color schemes.

Tapp Jobs – A premium theme designed by Press75. To use this theme, you also need to purchase a WordPress form plugin called Gravity Forms.

JobberPress – This theme is currently not available for purchase. As stated on its home page, JobberPress will be relaunched in near future.

Plugins:

WPJobBoard – This plugin is not free, you need to buy it for $97 and activate the plugin in your WordPress dashboard.

Job Listing – A free plugin that allows you to create a fully customizable job board. Meanwhile, you will get an affiliate id which would give you commission for any employer who posts a job.

Job Manager – This plugin offers you such features as manage job listings, create multiple job categories, and advanced filtering on job application forms.

WPCareers – This plugin allows you to build an online jobs/resume, and the applicants will be able to search, update, add/remove, and add or edit their resumes/profiles.

RecruitPress – Still under development; a beta release is tentatively scheduled for the first quarter of 2010.

Wowd, currently in Beta phase, is a search engine that helps users to discover what is popular on the Web.

However, Wowd’s search technology demonstrated to a very wide users that searching on the Web can works well on a peer to peer service principle.

In fact, Wowd’s primary founding idea was derived from Skype’s model. Unlike the leading search engine Google’s million of computer processors, Wowd want users to download its software to their computers in order to create a distributed network that will do the searching, as well as to distribute the Web pages they visited amongst all the Wowd users.

In this way, peer to peer data searching and sharing, no matter where its original Web page resided in; the Web pages will be pooled to the open search results that will benefit all of the Wowd’s users. Think of a Facebook public album that is currently can’t crawled by Google, when a Wowd user visited it, this particular Facebook album will show up on Wowd’s search result whenever a user want to search Facebook album.

For the users to get started in peer to peer searching; after the user downloading the software, Wowd suggests a user to reserve 2 gigabytes on hard drive so that the Web pages he / she visited can be stored and Wowd will update the visited Web pages accordingly. On the other hand, when a user searches for something, the software will then queries its neighbors, which ask for more neighbors, and so on, until the right search result is met.

However, on the downside, some said peer to peer searching will not work as this method is not fast enough and will not penetrate firewalls. Meanwhile, they also doubt how Wowd can convince people to download what really amounts to a voluntary piece of glorified spyware to their computers.

With more and more people joining Google Buzz for status updates, a third-party app, i.e. Buzzzy, known as the search engine for Google Buzz is vying to help make the user experience of Google Buzz become even more productive.

On Buzzzy, for any given query string on its search bar, it will generate results down the right-column that are updated in real-time from Google Buzz. Include in the search results are the avatar, the full name of the user, his / her profession, and a link to the original URL and its content (assuming the content is pull from an external service available on Google Buzz).

In addition, there is a nice feature offered by Buzzzy in which it list down the different timeline, source where the content are pulling from as well as the media (how many content is categorized under image, video, and URL link). This feature allows users to further filter their search results in a simple one-click process.

If you want a search engine that is real-time, and indexed conversations only, look no further than BackType.

On BackType, you can browse the popular topics, hot trends, or you can type in a query, hit the submit button, and voila! BackType will generate the search results based on the keyword in your query and they’ll only pull in conversations from blog posts (WordPress), Digg, Reddit, FriendFeed, Twitter and Hacker News.

In addition, BackType is building a scalable comments search engine. Although it’s akin to WordPress comment system, but with a broader reach to all the conversations indexed by BackType. Meanwhile, they have added few comment-like data sources such as Digg, Mahalo Answers, and etc.

Overall, their goal is to unlock as much as the underlying value in online conversations and comments across the Web.

To know more about BackType, it is founded in June 2008, also a startup that funded by Y Combinator and True Ventures.

Twine is a Web application that applied the common semantic model, based on the fact that human experts are expensive, and users on Twine can provide valuable search and data information.

On Twine, what they do is to provide a semantic Web environment whereby a user is given a profile page, and the ability to social bookmark any link or URL address as he/she like, and Twine will do the rest with its own semantic analysis.

Interestingly, Twine can help users in creating a data information library, discover all the bookmarks that they want to find out, but couldn’t achieve it by one’s own effort. With Twine, it will grouping all the interest things, stuff in an organized way, and thus, we’ll realize the real relationships of these things with our lives. But expect there is a huge volume of data information out there on the Web, it’s always impossible for us to expect Twine will perform well in categorization, classification and tagging automatically on all the data users enter to the site, but more advance their semantic technology evolve, the more it will understand human language, the perception on human towards language or computer code.

After you signing up to Twine, you can meet other users with similar interests, access to the data information collected by them via groups, etc. There are three main features offered by Twine: discover information that matter to users, collect and share bookmarks, and finally, receive recommendations based on interests.

In order to better understand a user’s interest, Twine has provided a “Add To Twine” bookmarklet (drag it to the browser’s toolbar) that enable users to directly add a Web page they like onto their “My Items” of their profile pages. The another way is to email your favorite Web pages through your own personal email address. Also, the Web pages you bookmarked are private, only if you purposely create your own public Twine, and add the Web pages you like to the public Twine, the bookmarks will be appeared as public in both “My Items” and public Twine.

The core of semantic technologies is to find and expose content. To achieve this aim, Twine also allowed users to explore “Top 100 Twines”, and “Top 100 Members.”

To know more about Twine, it is a project of Radar Networks: a startup that based in San Francisco.

TinEye is a reverse image search engine and is currently indexed more than 1.35 billion images from the Web. If you don’t know what is reverse image search, it’s akin to similar image search: by utilizing image recognition technology to help filter out search results.

For this functionality, users who search the images through this type of search engine are not search by text, instead they need to upload an image or type an image’s URL link to the search bar. This contrast with the conventional search engine approach, and TinEye potentially search all the images available on the Web and match the image that user uploaded, whether the images have been photoshoped.

From the results, you can compare the images one-by-one with the different pixel, format and the size of the pictures. Once you identify a particular picture better than the one you’ve just uploaded, you even can trace the original URL of the picture source and save it for your own use.

Try it out and compare the pictures yourself.