Imagine a situation where years of a brilliant mind are wasted on research that has already been done somewhere else. It happened because there was no way to find out if similar research had already been done.
The key person behind the origin of Google Scholar is Anurag Acharya. Since his college days at IIT Kharagpur, he has been anguished that great minds even at elite schools like IIT were not able to access already existing research material.
This problem got a solution, which we call Google Scholar. Since its inception in November 2004, it has come a long way. From time to time, many features have been added, and Google Scholar as a tool has matured.
Our goal in writing this article is to create a comprehensive guide to help you use the various features of Google Scholar to your advantage in finding patent and non-patent literature.
Most of us do not have the deep pockets to get an expert search from professionals. To address this very issue, I have started this HavingIP platform so that I can be of help by sharing my experience with those in need especially students, researchers, and small inventors.
Before you move ahead, we’d want to draw your attention to the in-depth guide written by us to search patent and non-patent literature on Google Patents, a tool that is free to use.
So, let’s start.
What can you find on Google Scholar?
Google Scholar includes journal and conference papers, theses and dissertations, academic publications, pre-prints, abstracts, technical reports, and other scholarly literature from a wide range of disciplines. Works from a wide range of academic publishers, professional organizations, and university archives, as well as scholarly publications available on the internet, are also included by Google Scholar. Moreover, it includes court decisions and patents. However, court decisions are restricted to the US only.
Search Operators in Google Scholar
|Search Operator||Its Function|
|AND||It limits search results. The search results contain both terms that are added with the operator ‘AND’. |
Example: vehicle AND antenna
This query returns search results that include both vehicle and antenna.
|OR||It needs to be in capital letters. It expands the search results. |
Example: dog OR cat
This query returns results containing a dog, a cat, or both.
|Minus (-)||It narrows down the results. It gives results that have the first term before minus and don’t have the second term after Minus. |
There should be space after the first term before Minus.
The Second term that is to be excluded should come immediately after the Minus sign “-”
Example: dog cat -lion
In this example, there is space after ‘cat’ i.e. the first term before minus and ‘lion’ i.e. second term has been used immediately after Minus.
This query returns results that do not contain the term “lion.”
|AROUND||It narrows down the results. It is a proximity operator. You should use it in capital letters. |
Example: dog cat AROUND (n) lion
The word ‘lion’ would appear in the results within ‘n’ words of the word ‘cat.’ The value of ‘n’ can be any positive number.
|Hyphen (-)||Example: A-B |
It uses no space between words and Hyphen or Minus. It shows a strong connection between the term ‘A’ & ‘B’.
Example: A -B
The use of a Hyphen or Minus this way would exclude the term ‘B’ from the results.
To use this operator, you must leave a space after the first term and use the second term immediately after the Hyphen or Minus without any space.
|Quotation Mark (“ ”)||It will return the phrase inside the quotation as it is in results. |
Example: “dog and cat going”
The search results returned by this query would include the phrase ‘dog and cat going’ as it is.
Syntax: intitle:search term
|This gives results that include the search term in the title. |
The term ‘dog’ will appear in the title of all results returned by this query.
Note: No space after colon ‘:’
|This gives results that include the search term in their body. |
The term “dog” will appear in the body of every result for this query.
Note: No space after colon ‘:’
Syntax: author:“first name last name”
|This gives results written by an author. |
Example: author:”john snow”
It will return results written by John Snow.
Note: No space after colon ‘:’, Put the whole name in (“ ”)
Syntax: source:”journal title”
|It gives results or articles which are from a source i.e. a journal. |
Example: source:”applied energy”
It will give results published in ‘applied energy’.
Note: No space after colon ‘:’, put the whole name in (“ ”)
Syntax: ininventor:”first name last name”
|It returns documents, including patents, that contain the name specified in the query as the inventor of a patent or the author of an article. |
Example: ininventor:”john snow”
From a first glance, it would seem that this query would return results that are only patent documents containing inventions invented by the mentioned inventor. However, in addition to patent documents, we also get articles authored by the name specified in this query.
Note: No space after colon ‘:’, put the whole name in (“ ”)
Syntax:”name of assignee”
|It returns patents assigned to the assignee specified in the query.|
It will patent documents in results where the assignee is Microsoft.
Note: No space after colon ‘:’, put the whole name in (“ ”)
Aside from search operators, Google Scholar also offers “advanced search,” as illustrated in Fig. 1 below:
Upon clicking the advance search button in the red box we get a pop-up screen as shown in the image below:
Advanced search in Fig. 2 provides features equivalent to what we access through some of the operators mentioned in Table 1 above. For e.g.,
|With all of the words||AND|
|With the exact phrase||(“ ”)|
|With at least one of the words||OR|
|Without the words||NOT or ( -)|
|Where my words occur: anywhere in the article||intext:”search term”|
|Where my words occur: in the title of the article||intitle:”search term”|
|Return articles authored by||author:”first name last name”|
|Return articles published in||source:”name of the journal”|
With the feature “Return articles dated between” you have the option to get results in a customized time frame. If you want to search documents since the earliest date available, you should leave the beginning date NIL or blank in the left box.
For example, the query Return articles dated between ” -2018″ in the advanced search pop screen as shown in fig. 2 above would return articles from the beginning to the year 2018. Here “beginning” means the earliest documents available in the Google Scholar database.
If you want to search from a date to present then leave the right box NIL or blank.
For example, the query Return articles dated between “1996- ” in the advanced search pop screen as shown in fig. 2 above would return articles dated from 1996 to the present.
After we run a query, we are presented with a page similar to the image below:
Box 1: Customize the time period
It facilitates the search over a customized period. For a quick search, it also gives readily available buttons like since 2018, since 2021, etc.
Box 2: Sorting
It provides sorting preferences. You can sort the result of a query by relevance or by date.
Box 3: Type of documents
It provides the facility to see documents of any type or of review articles.
Box 4: Include patents & citations
Here, Google Scholar has the facility to show patents and citations in the results as well. Normally, Google Scholar is used for document or non-patent literature searches, but very few realize that it can be a wonderful tool to get patents when other tools fail to provide the desired patent in search.
One such example we have discussed in this section of this article and we recommend you go through it to refine your search method.
Box 5: Create alert
When you search for a topic, e.g., “General Relativity”, you can set up an email alert by clicking on the envelope icon in the sidebar of the search result page.
Google Scholar has this feature to inform you about new results added to the search query. Further, it has the default option to select most relevant results for alert. However, you can also select “include less relevant” results for alert.
When you click on the envelope in Box 5 in Fig. 3 above, the page shown below appears on the screen:
By providing your email address, you can create an alert and receive periodic emails about newly published papers that match your search criteria.
Tips To Get The Most Out of Google Scholar
Google Scholar as a tool provides many feature which we normally do not use. Keeping few basic things in mind, we can increase the effectiveness of our search. What are those basic things? Let’s look at them.
- You can utilize “Cited by” to see the documents that referenced the article in question. This way you can further dig deep into the topic. See Box 1 in fig. 4.
- If you want to explore similar documents to that of a search result, you can click “Related articles”. See Box 2 in fig. 4.
- If you want to know other sources of the document, you can click “All versions” below the search result. See Box 3 in fig. 4.
- Sometimes there is a link to [PDF] to the right of the search result to directly get the pdf document. See Box 4 in fig. 4.
- If you are a new to the topic, first get some idea about the topic or subject from simple google searches, Wikipedia, thesaurus, etc. For example, if you want to search for ‘potato’ related articles, you don’t want to miss articles addressed to the scientific name of the potato which is ‘Solanum tuberosum’.
- If you have got very few results then you should try looking at the “Reference” section of relevant documents which is usually given at the end.
- “Related articles”, “Cited by”, and “Reference” sections can guide you to similar work that you are looking for. There is no single answer to reach your desired document. Keep exploring, you become better with practice.
- You can also cite some documents by clicking on “Cite” (See fig. 5 below). Upon clicking Cite, you will have a pop-up screen showing multiple styles of citation. Select one as you like and paste it into your working document.
Using the string author:”author name”, you can look for the profile of the author and articles written by him/ her. For example, we searched for Albert Einstein in Fig. 6 below.
After opening the profile of the author, you can get the documents authored by him. In addition to this, you will also get the data (See right side in fig. 7 below) regarding his documents cited by others over the period of time, h-index, and i10-index.
Further, if you want to know the trend of citations over the period of time to understand the impact of the research of a particular author, you can do so by clicking “view all” in the red box in fig. 7 above. As a result, you will see a pop-up screen as shown in fig. 8 below:
From Fig. 8 above, you can observe that the work of genius Albert Einstein is getting cited decades after he has gone. In fact, it appears that his work is more relevant now than ever before, as he is being referenced more and more in recent years. In fact, as per Fig. 7, since 2017, his h-index and i10-index have been going up exceptionally well.
Many times, it happens that you come across a good document in a search result that you want to reference in the future. Keeping this in mind, Google Scholar provides a feature to save the search result and even allows you to label it.
You can save the results of your search in “My Library” for future purposes. In order to save the search result, you have to click on the “Save” button in the red box in Fig. 9. Once you click Save, you get the pop-up screen, as shown in Fig. 9.
In My Library provided by Google Scholar, you can label the documents to various lists made by you. For example, see the Reading list in Fig. 9.
Once you have saved the document, you can access the same through the “My Library” button provided in the right corner of Google Scholar as shown in fig. 10 in the red box.
Fig. 11 shows how does My Library Looks like. It has two labels created by me. One label is “Manage” which consists of one document titled Management. Another label is “Reading list” which also consists of one document titled General Relativity.
You can search the documents in My Library if the number of documents saved there is large.
How To Use Keywords In Smart Way To Find Desired Results From Google Scholar
Google Scholar is the most unusual yet effective patent search engine. In my experience, I find Google Scholar one of the best tools for searching patent and non-patent literature, and it never fails to amaze me.
What makes it best is that it may give you results in minutes, sometimes just by putting 2–3 right keywords in the search box. At this point, you may be wondering, “What do I mean by it?”
Let’s understand the magic of Google Scholar through an example.
Suppose we are given the task of finding prior art for a patent claim. The claim essentially has the following two features:
1. Vehicle lights are switched on automatically when its engine starts.
2. The vehicle lights are switched off automatically when its engine shuts down.
We could make a search query using keywords like vehicle, light, engine, automatic, start, shut down, switch on, and switch off to be searched in Google Scholar.
So, let’s start with a query as vehicle light engine automatic start shut-down
If we do some thinking, we’d see that if write automatic engine in a query, it’d mean that documents that have engine start and engine shut down features will be included in the results.
That is so because the presence of two keywords “automatic” and “engine” in the proximity of each other in a document would very likely point to three things: 1. engine may do something., 2. something is happening automatically, and 3. these two events are related.
Since the engine is doing something, It may very well be related to starting and shutting down. This type of thinking is very necessary while doing a keyword search in any search tool. Because it is important to weed out redundant keywords.
This comes with experience, nothing is perfect in a search. There may be a chance when using redundant keywords, you may get a quick result but it should not be your preferred approach.
So, we now come up with the query vehicle light engine automatic
Our aim is to reduce the query to only 2–3 keywords. So, we would start thinking about removing ‘vehicle’ from the query. Now the query remains “light engine automatic”. In such a case chances are that:
- The scope of results widens. Many of the results would not be related to vehicles.
- Some of the results might fetch software engine-related literature, the search engine for example.
- Some of the results fetched might be related to a light engine- an LED equivalent of a conventional lamp.
Note: By the time you search these queries, it is very well possible that type of results change. That is because Google algorithm always learns and improves. What's important here is that you understand the thought process behind using and removing some of the keywords in a query.
This time we remove the term “automatic” and add “vehicle” to come up with the query “vehicle light engine”. In such a case:
- The scope of the results would widen. Many of the results would not be related to the headlight of the vehicle.
- Some of the fetched results might be related to light engines or light vehicles in terms of weight.
- Some of the fetched results might be related to various kinds of other lights, traffic lights, for example, and not particularly to the vehicle headlamp.
Next, we remove the word automatic. So we now have the query as “light engine”. In this case, we observe the scope of the results widens even more.
Further, the expression ‘light engine’ also gives the impression of the engine having less weight. So, engine weight-related results also pop up.
Other types of results would be related to a light engine—an LED equivalent of a conventional lamp, which we have in attempt 2 already.
After exploring the possibilities, if we can come up with 2-3 keywords that express the essence of the invention, Google Scholar usually gives a good prior art.
So, what should be the thought process, while deciding what keywords to choose?
So, we need to think of a keyword that can help us reduce the number of keywords in a query while still conveying the meaning of what we are looking for.
For example, if we use the keyword “headlight,” it indicates a light at the front of a vehicle.
If we use “engine” and “headlight” in a search query, there is a high chance that the document having both keywords will be relevant to our invention.
Because any document having both ‘headlight’ and ‘engine’ would have a relation of vehicle light at the front with the engine.
So, there is a high chance that the operation of the engine and the operation of the light at the front of the vehicle may have some relationship.
So, we would use “headlight engine” in the search query and voila, we get relevant results.
This may not work every time, and it may not be easy every time. However, the thought process we just followed in deciding keywords is always an asset and comes with experience.
To decide on keywords, you may do a simple google search, read Wikipedia, and check out Thesaurus. This way, you will get a good understanding of the topic which you are searching for and you get the idea of keywords that you didn’t know in the first place.
As you proceed with your search and come across many relevant documents, your understanding of the topic and therefore keywords will get refined eventually which will lead you to the most relevant search result.
What is h-index?
The h-index of a publication is the largest number h such that at least h articles in that publication were cited at least h times each.
For e.g., a publication has 5 articles. So, if we talk about individual articles that were cited 16, 11, 7, 3, and 2 times, respectively, the publication would have an h-index of 3.
What does h=3 mean here?
It simply means that at least 3 articles from the publication were cited at least 3 times. It doesn’t say how many articles are in a publication.
Let’s take another example, suppose you have an h-index of 40 then, you have at least 40 articles/ papers with at least 40 citations each.
h-index was suggested by Jorge E. Hirsch. According to him, after 20 years of research work, for a researcher to have, an h-index of 20 is good, 40 is outstanding, and 60 is truly exceptional.
You can access Hirsch’s paper which talks about the h-index to quantify the scientific research output of an individual.
What is i10-index?
It is a simple index relatively and is only used by Google Scholar. It indicates the number of publications with at least 10 citations.
So, how do you calculate an i10-index?
To answer this question, suppose you have 8 articles in total and those articles have been cited 19, 26, 3, 11, 5, 10, 26, and 13 times by others, respectively. So, you have 6 articles that have received at least 10 citations from others. This implies that you have an i10-index of 6.
For many years, Google Scholar has been my go-to search tool preferred over other paid and unpaid databases. It is so because once you get hold of it, it can deliver you unexpected success in your search. The simplicity of this tool is a sure attraction to anyone.
Behind creating this best available guide on the internet for Google Scholar Search, our aim was to empower common researchers, inventors, students, and academicians who don’t have the luxury to pay for expert searches from professionals.
We have looked at Google Scholar through two lenses. One lens has come from Google’s manuals and instructions. Another lens has emerged from my and my colleagues’ experiences. I hope you have gained something worthy of your time
In the series of search guides for the tools available for free, we have written Google Patents: An Ultimate Guide To Search. If you want to further continue your learning spree, you can refer here for more such articles.