iQser: taking information management to the next level

By | February 2, 2015

Late last year, I joined iQser – a relatively young company, but with a brilliant technological basis, of which information retrieval is just one particular application. I expect we'll see them post several more applications in the near future.

iQser focuses on semantic middleware. It extracts meaning out of information and connects relevant bits of information. In my eyes, what makes it unique is rather how it approaches information connectivity:

Context is the primary factor behind data relationships. You've heard this many times, I'm sure, and I'm also sure that you will not dispute the importance of context in understanding data. But unlike many technical definitions where context involves physical location, device, friends, time, or other such factors to determine a user's context – meaning that the true working context is just a best guess based on these categorized criteria. iQser's approach focuses primarily on the information you're currently working with to determine your context. Instead, if you have a word document open, then that document constitutes your context: it defines the topic, the depth, the scope, the language, and a whole lot of other linguistic and content-related factors related to the context that you'd intuitively expect to define your context.

Dynamic adaption is built into the core of the technology. Language changes over time, and most static systems can't keep up with new memes, terms, and concepts evolving in a living community. So, iQser adopts a dynamic, bottom-up approach to connecting data as opposed to a static, top down approach – allowing it to pick up on and reflect these changes on-the-fly, learning from every interaction and collaboration producing data of any sort.

Speed, performance, and big data. I'll be frank here: most semantic technologies break down after a certain data set size. Indexing Wikipedia is a favorite among researchers, but Wikipedia is a small dataset in comparison to what most large enterprises generate on a daily basis. You'll find that in the fine print of almost every semantic technology on the market today. But a semantic technology that is actually built for and optimized for big, real-time data processing in a production enterprise setting? That's rare. I invite you to have to look into the system architecture and test the technology yourself – after all, it is a daring claim, and the best proof is one that you see yourself. As the ancient wisdom goes, seeing is believing!

And that's what I find very exciting – the potential in this technology as an information bus, linking enterprise information, systems, processes, workflows, and policies, building a backbone to an information ecosystem driving analytics, intelligence, applications, as well as all of the daily operations taking place today. A solution that is simple, fast and easy to roll out, and that can serve business needs not just in 2015, but also for the foreseeable digital future.

Originally shared by +iQser GmbH

Search reloaded: a faster and better redesign of the search process
A new approach to information with higher productivity and higher quality

Let's face it: search, despite being a valuable tool in finding information, is actually a rather ineffective way of consolidating information. Consider the amount of mental power required to conduct a search as part of a research effort: you need to think about what you want to find, enter that phrase in a search engine, sift through results, and then hope that your search phrase was structured appropriately to hit all of the relevant information that you need. That's a lot of thinking on the way. And, since technology has come a long way since the first search engine – and can even distill and write news articles that can't be differentiated from human-written articles, shouldn't there be something better than search for the rest of us?

The answer is yes: there is. It's called context-sensitive information retrieval, or "context search". Context search isn't a true search, because you don't have to know what you want. You just need to know that you want more information. Then, it's up to the underlying technology to interpret your current working context, distill available information sources to match your that context, and deliver you with an overview of all relevant and important information for you to process – even essential information that you might not have thought of in a typical keyword search.

The result is a simplified process for doing knowledge work: fewer process steps, and higher quality results. This translates into increased productivity, higher quality, more transparency, and direct cost savings.

You'll be surprised by the simplicity, ingenuity, and effectiveness of this methodology. But enough teasing. Here you have it: the detailed explanation behind it all:

Does this sound like something that could take some pain out of your life? If so, we'd love to work with you!


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