Search has many parts, pieces and players in both the software and the technology.
A search engine is different from search software. The terms are used interchangeably by people, but they are not the same. Search software is an application and a search engine is a collection of servers with large amounts of data on it that is indexing the Internet and delivering it by HTML pages to customers.
A recommender system is a information filtering system that seeks to predict the rating or preference that a user would give to an item.
Recommender systems have become increasingly popular and are utilized in a variety of areas including movies, music, news, etc.
What makes a search engine different from a recommender system? Everyone who spends time surfing the web comes into regular contact with both search engines and recommender systems, whether they know it or not.
These two communities are related and even more so as search engines become more advanced and comprehensive. Many now include lessons learned from information filtering techniques and recommender systems. It’s becoming less relevant to distinguish search engines and recommender systems based on their underlying technologies.
To make the differentiation between the two technologies, consider whether you asked for the information. In a search engine, there is a query box where you type in what you’re looking for and they bring back a list of results. From large search engines like Google to the limited search boxes that index the contents of a single page, they all have query boxes.
In a recommender system, content has just appeared on your screen that is relevant to you but you didn’t request it. Recommendation systems are all around us. Ecommerce companies like Amazon recommend goods that we are likely to buy based on our past behavior. Netflix suggests what videos we should watch. Pandora even builds personalized music streams, based on what we are likely to listen to. Almost every website has a recommendation system based on user browsing history, past purchases, past searches, and preferences.
Both search engines and recommender systems can provide personalized content that matches your needs, but it’s not what they do or the magic that they use to do it, but more how you interact with them that distinguishes them from one another.
Access Innovations is one of a very small number of companies able to help its clients generate ANSI/ISO/W3C-compliant taxonomies and associated rule bases for machine-assisted indexing.
Melody K. Smith
Sponsored by Access Innovations, the world leader in taxonomies, metadata, and semantic enrichment to make your content findable.