1. Fuzzy Searches
Fuzzy searching allows you to search for words with similar spelling to the entered search word. It can be a useful way to ensure that you don’t miss search terms that have been misspelled or spelled in a different way than you anticipated.

2. How does it work?
Depending on the database parser you are using, fuzzy search might be activated by adding a symbol like the tilde (~) to the end of a term. For example, if you wanted to search for a term similar in spelling to roam, you would enter roam~. This would also search for words such as foam and roams. You might even be able to determine the degree of similarity to the original term. For example, you might be able to enter a value between 0 and 1, for example roam ~0.8. The higher the value, the greater the degree of similarity.

3. Proximity Operator
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Shane is an inventor who’s searching a patent database system for a stand that supports a bicycle. But, when he searched for bicycle stand, it produced a number of false drops.

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So, he decided to use a proximity operator and search for “bicycle stand”~2.

5. But, what could Shane do if he was only interested in the words bicycle and stand next to each other – and in that order (since stand bicycle will not do) ?
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6. A bit more specific:
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If Shane wanted to restrict the search to just what he needs, he could use the phrase “bicycle stand”, enclosed in double quotation marks. This creates a phrase and everything within those quotes will be searched as a single term.
So, it can be concluded that,
Search terms, single keywords or phrases may be combined using Boolean operators.

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Go through the next table and make sure you know that the search results are retrieved by selecting the proper options.

8. Metal AND cutting Metal NEAR cutting Metal cutting Metal NOT cutting
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Search Result
Search Query
Documents with words “ metal” and cutting anywhere in the document
Documents with metal and cutting close to each other
Documents with phrase “ cutting metal”
Documents with phrase metal cutting
Documents with word “ metal” only
Documents with word cutting only
Metal AND cutting
Metal NEAR cutting
Metal cutting
Metal NOT cutting
Metal XOR cutting

9. Documents containing the word solar
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Let’s imagine we wanted to retrieve documents related to solar power or wind power. Thus, following kind of documents the search solar OR wind AND power retrieve :
Documents containing the word solar
Documents containing the words solar and wind
Documents containing the words solar and power
Documents containing the words solar, wind and power
Thus, it is clear that many database systems will treat operators from left to right, so the word ‘power’ would have to be in the results. But we can’t really be sure.

10. Dealing with ambiguity
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Suppose, you want to make sure that your search is clear. But, some search queries that mix different Boolean operators can be ambiguous. How will you tackle this? Let’s take a tour of some important points in order to avoid such ambiguities.

11. Multiple meanings:
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The query solar Or wind AND turbine could be interpreted to mean either:
Solar OR (wind AND turbine) – this means documents would be retrieved having either the word solar, or the words wind AND turbine.
(solar OR wind) AND turbine – this means documents would be retrieved having either the word wind or solar, and the word turbine.

12. Different interpretations
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The order in which different operators – AND, OR etc. – are applied may vary between database systems, with the result that different systems may interpret the search query in a different way, with one system carrying out the first search, and another carrying out the second search.

13. Being clear,
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In order to avoid such ambiguities, parentheses (i.e. brackets) are used to organise search queries. The use of parentheses in this way is called nesting (or alternatively grouping).

14. Wind OR (solar AND turbine) (Wind OR solar) AND turbine
Depending on what you’re actually looking for, the search query will then be either:
Wind OR (solar AND turbine)
(Wind OR solar) AND turbine
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15. Fields
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16. You should now be more familiar with some of the tools available to help you construct search queries: keywords, classifications, operators, etc. There is also a wide range of choices available to you when deciding in which parts of a patent document – or in which fields – these tools can be used.
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17. Basic fields There are various elements of a patent document,
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There are various elements of a patent document,
Names of inventors and applicants
Application and publication numbers
Priority data
Classifications
Titles, descriptions, claims
Other elements such as designated texts
You can use each of these elements as an individual field in which to direct a search. Other fields such as fields for the languages of filing or publication may also be available.

18. Derived fields
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Derived fields may be constructed within a database system by combining individual fields. For example, a derived field may be constructed using all the information on the front page of a patent document (including title and abstract but also applicant and inventor data) or all names (including both applicant and inventor names).

19. Field searches:
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There are a number of ways you can choose and combine the fields you want to include in your search. Let us know this !

20. Most online patent database systems allow you to search using given fields. This is simply done by entering your search terms and selecting the preset fields you want to search. For example, you could enter electric car and choose a front page search. In PATENTSCOPE, this would then search for the terms electric and car within a number of fields. In this case, the individual fields searched would be the title, abstract, IPC, numbers and names fields.
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21. You could widen your results by choosing to search any field
You could widen your results by choosing to search any field. This would search all the fields of a patent document and return the widest set of results. Or, if you wanted to limit your search right down to the IPC, you could choose to search this specifically. This pre-set field searches will differ between database systems but they will allow you to search a number of different combinations of fields and tailor your search. However, you may want to define your search fields more precisely. Let us know how to do this…
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22. Command line searches What does it let you do?
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Some online patent database systems will also give you the option to search using a command line search interface.
What does it let you do?
This type of interface, such as the Advanced Search feature in PATENTSCOPE, has the advantage of allowing you to be more flexible in your search strategy.
A command line interface will typically let you create search queries by entering the appropriate code for a given field and the associated search term. But they do require you to learn the specific language of the database system, in particular which field codes are used.

23. What are field codes?
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The field code is a two letter code that represents an individual field to search. These may differ slightly in the different patent database systems.
For example, in PATENTSCOPE, TI represents the title, AB represents the abstract and IC represents the IPC.

24. How do you separate terms?
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In this type of search, the field code and the search term need to be separated by a character such as a colon (:) or a slash (/). Again, this depends on the patent database system. So, if you want to search for the term power in titles of patent documents, you might have to enter: TI:power or TI/power. We can also put field code after the search, e.g., power:TI. One should avoid spaces between the search term and field code. Boolean operators can also be used such as, TI:(power AND engine).

25. TI:(Solar OR photovoltaic)
If we want to carry out a command line search for documents with the terms solar or photovoltaic in their titles, following structure is used:
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TI:(Solar OR photovoltaic)

26. TI:(solar OR photovoltaic) OR AB:(solar OR photovoltaic)
If we want to search the abstracts of documents as well as titles, we will use:
TI:(solar OR photovoltaic) OR AB:(solar OR photovoltaic)
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27. Refresh We have learnt: Smooth operators It’s all in the phrase
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Refresh
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We have learnt:
Smooth operators
It’s all in the phrase
Using fields
Nesting
Wildcards
It’s fuzzy