A review of online tools utilizing semantic search.
As the Internet evolves, exciting new types of search engines are developing, providing researchers with valuable enhancements to their search experiences. Assorted tools are especially useful for information professionals and knowledge workers. Such features as real-time mathematical computations, semantic interpretation and automatic indexing/tagging/categorizing of results sets are now available in many online tools.
Examples of Semantic Search Engines
Perhaps one of the more popular and longest-existing semantic search engines is DuckDuckGo. This search engine has an interesting feature of the search results page whereby it shows “Meaning.” For example, if a user types in “Amazon,” the “Meaning” area of the page will show the differing search pathways: Amazon.com, the Amazon Rainforest, the Amazon River and even Amazon women. The searcher can then navigate to his/her topic of choice, avoiding irrelevant hits.
Yippy provides what are called “Concept Clusters” when given keywords are searched. A search for “mobile payments” will show “Concept Clusters” of “Banking,” “China,” “Restaurants” or “Credit Cards,” for example. The number of hits is noted after each cluster. This manner of display helps the user to quickly gauge the totality of the results in order to precisely explore the data of interest.
Deep Web Technologies offers its BizNar search engine, which provides immediate indexing and categorization of search hits. For example, if a user searches “fracking,” the results page shows convenient topic buckets for various types of fracking, like hydraulic, energy or natural gas. Authors, publications and dates are also indexed, along with “counts” of hits, so that a researcher can click on only 2014 results or see who the top Web content author regarding the topic is.
The Washington Post profiled a search engine called Omnity that they described as possibly being “smarter than Google.” This self-described “knowledge discovery engine” searches context as opposed to keywords. A free basic account or paid access options are available. The results list provides visualized answers such as word clouds and scatter plots that count the type of hits that match the concept, such as number of news resources and number of Wikipedia resources. One especially useful aspect of this search engine is that the results list bibliography can be immediately created into a PDF document.
Wolfram Alpha is an interesting computational knowledge portal whereby users can search for free form keywords and concepts and the results will show curated, targeted results. The curated collections include statistical, linguistic, mathematical, cultural, financial and historical data sets. The results lists often appear as concise data points like real-time currency conversions, financial line graphs and even dynamic computations.
Search Engines of the Future
The future may bring some exciting tools and technologies for search engines. Apple is reported to be bringing the Siri technology to their desktop computers. A person may simply have to say “Siri, search the Web for…” and a results list with assorted Internet hits will show on the screen. Whether this tool will be sophisticated enough to understand the semantics of advanced search needs like “Boolean notting out” results that are irrelevant or sorting the results in some way, remains to be seen.
New technologies to connect with data from Internet of Things (IoT) devices, called Resource Directories, are also in development. These search engines will have IoT devices registered with them and will be able to glean data from these entities. This type of search engine will be accessible to only authorized searchers who have clearance to examine the data from the IoT devices. The search capacity and sophisticated features of future search engines may bring data to the fingertips of researchers, which only a few years ago, was impossible.
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