Search Basics

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The Fundies

Search Approach

Performing a search using (Digger) is easy, but with a little additional information, your experience can be greatly enhanced. Digger is a "Semantic Search Engine ". At the core, this means that the Digger engine is much more sophisticated than key word search engines, and is able to derive the intent of your query through semantic analysis, and go on to perform much of this advanced analysis automatically, though we do allow for you to easily inject human intelligence directly into the search process as well.

What does it all mean?

Well, Digger can perform navigational searches - those that attempt to get at a specific reference, like a name or address.

Example: {Add a search box example graphic}

But Digger really shines when the search query is what we term a discovery search . Discovery searches are much less navigational, and rely on semantic understanding of the intent of the researcher. As a result, the underlying query processing is much more complex than traditional key word based search engines like Google.

Example: {Add a search box example graphic}


Don't be concerned about capitalization in your query - searches using Digger are NOT case sensitive. Any combination of upper and lower case letters will generate the same results for your query. For example: san jose, SAN JOSE, San Jose, or even SaN jOsE all generate the same results.

Search Term Processing - "ANDs" and "ORs"

The Digger semantic search engine goes far beyond basic search engines in use today.

Example Query: Term_A Term_B

Nominally, this query is requesting results for pages that contain both "Term_A and Term_B". Digger automatically includes the AND logic on your behalf, but it does much more. Let's say, that Term_B also has a strong semantic linkage to another word, say "Synonym_B". Digger will automatically construct additional logic to search for the original conditions and generate additional logic to search for "Term_A AND Synonym_B" as well. The full expansion of this query then becomes: (Term_A AND Term_B) OR (Term_A AND Synonym_B). Through semantic analysis, a much richer search query is automatically generated without any additional manual work by the researcher. These, and several other semantic optimizations are performed automatically by Digger - you as the researcher, are freed from constructing complicated Boolean queries to get at the actual intent of your search.

Exact Phrase Searches

Whenever you enter a set of multiple terms enclosed in double quotes, Digger interprets this as an exact phrase search and looks for only those pages that contain the phrase exactly, without any intervening words. Example Query (1) below will return only pages that have this famous phrase, exactly as Patrick Henry uttered the words on March 23, 1775. Example Query (2) below will return only pages that contain BOTH the exact famous phrase from Hamlet and a reference to Shakespeare himself.

Example Query (1): "Give me liberty or give me death"
Example Query (2): "To be or not to be" Shakespeare

Because You Asked ... Here are the Other Major Differences from the Google "Search Engine"

It is important to recognize that Google (the company) offers several applications that are not actually part of their core search technology. This can be confusing, since several of these applications or tools are accessed through the Google search engine main page. Digger, on the other hand, is focused on the automation of high quality semantic searches - finding what you intended, and doing so through an automated application of sophisticated technology and process methods. In addition, TextDigger, Inc. has several other sophisticated Products which may be used separately or in conjunction with Digger to address several different applications of semantic analysis to searching, tagging, content understanding and others.

Because of these fundamental different approaches, there are differences in what the two search engines accept as input, and how they ultimately process that input. A quick summary of the key differences are provided by conveniently grouped categories below.

Classic Query Operators

AND , OR , and " ... " (quoted phrases) are supported by both Google and Digger, but Digger automates a far more sophisticated range of these than is possible with the Google interface, which, if attempted at all, would require a significant amount of manual effort on the part of the researcher. As simple example of this can be seen in Search Term Processing - "ANDs" and "ORs" above.

Extended Query Operators

-<usage> , and ~target_Term modifying_Terms are supported by both search engines, but again, Digger capabilities are either automated, broader in capability, or both in comparison to the Google search engine.

Example : Negative Context:
Google Example: dog -animal

Google View: Find pages that contain the word dog, but not animal. The result will contain many, non-related context results, extracting only the animal sense. If what I really mean is the shortened form of "hot dog", I'll need to refine this search many times to get a good result set.
Digger Example: dog (and selecting a "sense" to constrain by any number of context conditions)

Digger View: Easily tailor the search to the intended meaning of dog through the selection of one of several "Sense" attributes automatically generated by the Digger analyzer. On the first query, the Sense selection will drive the query directly to entries about "hot dogs".
Example : Single Term Synonym Search:
Google Example: ~auto loan repossession

Google View: Find pages that that contain the keywords "loan AND repossession" AND the term "auto" or its synonyms.
Digger Example: auto loan repossession

Digger View: Without any additional notation (e.g., "~"), Digger will automate the inclusion of true synonyms for "auto", AND it will generate results regarding further semantic analysis on the other terms.

Calculator Operators

+ , - , * , / , % of , and ^ essentially turn the Google "search engine" into a calculator, and do not perform any search function whatsoever.

TextDigger is focused on semantic search, and therefore this type of input would generate meaningless results.

Navigation Operators

site: , [#]...[#] , link: , info: , and related: are all operators processed through the Google search engine that are available as specific navigational hints to the search engine to override the default processing of the Google search engine. These are not semantic in nature, and therefore are not processed by the Digger engine.

Miscellaneous Operations

Google Example: red * blue
Google View: Find pages that have the word "red" and "blue" separated by 1 or more words.
Digger View: This has no contextual meaning and is not supported in Digger.

Google Example: +Term
Google View: Find pages contain the keyword "Term" but NO plurals, tenses or synonyms.
Digger View: Not supported.

Google Example: define:Term
Google View: Return the definition of "Term".
Digger View: This is not an issue of semantics, and is not supported by Digger.