This is how antiquated statistically-based, popularity-driven search devices like Google’s “page rank” work. Search for just Apple in Google and most of the top results will be about the company, not the other two, because most Google users search and click on results about Apple Inc. Perhaps an even simpler example would be to tell the difference between Apple the fruit, Apple the company (or products), and Apple the record studio. In simple terms, a perfect semantic search engine would instantly and automatically take into consideration the meaning behind your question or “search string.” For example, it could disambiguate results that lead to people’s profiles from, say, the text in employment advertising: it would serve up only the profiles to recruiters and the employment ads to job seekers. Meaning, that is, as it is inherent in symbols, words, phrases, sentences, and larger blocks of text. Semantics is defined as the field of study that focuses on meaning. This is different from the concept of a Semantic Web, which consists of highly structured data such as XML. In short, Semantic Search applies grammatical analysis, logical interpretation, and linguistic morphology in the identification of concepts from unstructured data. The application of semantic technology shifts search from browsing for relevant documents to discovering relationships between content and delivering actionable information with insights. In contrast, Semantic Search technologies look for the concept that is being searched for rather than specific keyword(s)’s or synonym(s)’s occurrence in a document. These efforts only begin to approach true Semantic Search capabilities and today are limited to providing only a basic understanding of associations and concepts related to a search. Major search engines constantly experiment with ways to simplify search, moving away from complex Boolean queries and the use of advanced field search syntax, in an effort to assist users in quickly finding what they seek. This whitepaper explains Semantic Search for candidate sourcing. Many expert communities talk about Semantic Search applications being the most likely technology to deliver this kind of result, but few take the time to explain it in plain language. In an ideal world a search engine would function like a human, understanding the underlying meaning of the user’s search and then matching the search results accordingly. Unfortunately, today’s search engines are still inefficient, delivering mismatched information and requiring complex search string knowledge to use effectively. Without a good search engine, you simply get lost in all the information. Most people agree that the biggest problem with online recruiting today is too much available information. That is, until the promise of Semantic Search. Search can be as simple or complex as we want it to be, but at the end of the day we are limited only to words in the fields of a database. That’s what recruiters and sourcers often misconstrue as “Boolean search.” In fact, the only Booleans used are the assumed AND between every search term, the occasional OR as with (intitle:resume OR inurl:resume), and the rare use of the NOT or AND NOT when applying negative search terms such as -jobs or -submit. The “big search engines” also use fields and they share some in common, such as intitle, inurl, site, and filetype.
You use fields to search your Outlook when you ask for people with a specific name or when you query by “job title” on Monster or LinkedIn. When searching a database what we search are “fields ” for example, “Company Name,” “Email Address,” and so on. Each “database” (lumping in Monster, Google, LinkedIn, and Facebook under that term) has its own set of field search commands. Search syntax has been around since the beginning of databases. When recruiters talk about “Boolean search” what they are really talking about is creating search strings, sometimes using advanced commands or complex search syntax to query specific fields inside of databases.Bottom line is that when you use OR the result is “true” whenever one or more of the words are matched. In English grammar or is a coordinating conjunction, and in ordinary language it sometimes has the meaning of an exclusive disjunction. The The OR is called a logical disjunction, sometimes an inclusive disjunction or alternation in mathematics. In search engines you don’t need the AND because its always assumed by default, so forget about it. Booleans are simply three LOGICAL OPERATORS: AND OR NOT.There is just too much confusion about so-called “Boolean search” so I’d like to clarify a few basic things:
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