Information retrieval is now a central part of daily life, in and outside of the workplace. In an abundance of stored information, effective querying is what allows us to make any use of the multitude of data present all around us. The term “knowledge worker” is applied broadly, but in every sense, modern knowledge workers are united by the reliance on retrieving and using information. At the heart of information retrieval is search.
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A brief history of retrieving information
The concept of easily accessing information now has an amplified importance, but a tool akin to search software is the natural wish of anyone who has faced the daunting task of sifting through an unfathomably large catalogue of information. Historically, information retrieval predates Greek and Roman literature. In these instances, searching content was aided by structuring the materials into books and chapters. It is here that we see evidence of a table of contents and indexes emerging to guide the reader quickly to subjects.
For collections of works, cataloguing schemes, such as those that embody the conventional management of large information stores, are millennia old. Eventually, the amount of information at hand necessitated the emergence of new search technologies. In the 1800s, came the advent of mechanised search tools, which in turn became computational in the mid 1900s. The theory of indexing and cataloguing information for effective retrieval and search today bears fundamental similarities to age-old tradition, albeit with the human legwork replaced for inconceivably fast, computational operations.
How do we search?
Information retrieval, and thereby search software, is oriented around a number of different mathematical bases, depending on the completeness of the information provided and the strictness placed on matching criteria. In data retrieval, a specific piece of data is predominantly sought. Boolean matching, a true or false check, establishes if a piece of information stored exactly satisfies the search query. In information retrieval, the completeness of the search query begins to become more partial. While data retrieval is the bare-bones search, information retrieval, and to a greater extent, knowledge retrieval, incorporate extended logic in attempts to retrieve results that satisfy the expectations of human thinking.
Simple task, subtle nuances
At its core, search is a very simple concept. It is a tool that queries a catalogue of information and retrieves what information in the collection matches. The business of search, however, has become a very complex one. Search software is far from perfect. The human mind does not operate in a manner similar to most search engines. Research and development in search software largely has a focus on extending the basic logic of search, to better approximate human, associative patterns of thinking.
There have been, and continue to be, amazing developments in the science of search. Gradually, these establish themselves as essential and propagate search software advancement. Unfortunately, as the human brain remains a new frontier of exploration, trying to mimic human thinking can become a far from exact, hit-or-miss task, which can result in some truly awful search experiences. One has to be very wary, pushing a technology still in its infancy on an unsuspecting user-base.
Where is my search software?
In a 2014 industry watch report, 71% of companies polled thought search software was important, yet only 18% have cross-repository search software tools. The value of search is self-evident; hence the absence of search software in modern companies is more astounding. Desktop search software is a useful productivity tool. However, it is in enterprises where productivity gains per employee add up to a truly significant productivity increase.
Complaints about enterprise search software are in no short supply. A common trap appears to be attempting too much, too new and too “earth-shaking”. A consequence of this is primarily search software systems that do too little effectively. The idea of moulding search software to fit users is always a solid footing, however, theory can be exceedingly difficult to implement in practice. Most of us are already quite familiar with how basic search software works. A result of this is that new, apparently user-friendly systems can actually force the search user to adopt new behaviour. Mass users need better search tools that integrate seamlessly into their daily routine, not new learning curves. Maybe, at the end of the day, a simple, robust search tool is what you are looking for.