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XLSCOUT contains 130 million+ documents and 200 million+ research publications. XLSCOUTTM database has a coverage of 45 jurisdictions in full text and coverage of 100+ jurisdictions with bibliographic details.
XLSCOUT came up with a unique approach where we developed a proprietary corpus of technical concepts containing more than 3 billion words with over 100 GB of processed data. The corpus has been developed on a Machine learning model trained with 200+ machine hours.
XLSCOUT is a research-based, AI-driven patent analysis and research platform that utilizes trained technology data to provide insights. Using advanced technologies like NLP, Machine Learning, and Artificial Intelligence, XLSCOUT eliminates the pain of manually going through humongous patent and publication datasets.
XLSCOUT novelty checker is an AI-based tool which enables you to test the novelty of your idea. One can enter their ideas in natural language and examine related prior art. The tool also helps you to generate a quick report which can be used for a first pass analysis.
Unlike other databases novelty checker enables you to conduct a first pass patentability search by entering your idea in a simple language. There is no need to make queries.
In order to conduct a search through novelty checker just enter your idea and disclosure in the first step in natural language. The disclosure should explain your idea and should include a novel part of your idea. The invention title should be broad enough to cover the entire disclosure.
The invention title should be broad enough to cover the entire disclosure. In the disclosure part, avoid using repetitive sentences. Disclosure should include novel parts of an idea disclosure.
Advanced search parameters help you to supervise the search. Using advanced search parameters you can direct the tool to conduct a search in a certain way. Options like entering a focus keyword or a noise keyword can help you refine your search. One can also apply a date range and include classifications in your search. Using advanced search parameters is completely optional and depends on the requirement.
Conducting a search through Novelty Checker involves going through four steps. The foremost important step is that of entering the invention title and disclosure. Further steps involve star marking key features, selecting relevant technology domains, and selecting key variations. The main and compulsory step is step 1 that of entering disclosure and invention title. All other steps are optional.
The breakdown of your idea disclosure into key features enables you to direct the tool to put special emphasis on that particular key feature. The tool applies Natural Language processing at this step to understand the contextual meaning of the idea.
Star marking key features puts emphasis on those particular key features. Exclusive queries are made on those key features which you have star marked.
Star marking key features directs the tool to put special emphasis on those which are star marked. However, this doesn’t imply that other key features will be ignored while conducting a search. All key features are taken into consideration by default.
In step 3 the tool fetches relevant classifications/technology domains in which your idea might fall into.
The tool is able to fetch and suggest relevant classifications as it applies a machine learning algorithm at this step. The tool has been trained on existing patent data and has learned the correlation between existing patents and their classifications.
Selecting relevant classification can impact your result set largely and also increases the chances of very relevant prior art being included in the result set. This step can also impact the ordering of results. One should select only those classifications which seem directly relevant and only if you are sure about. Selecting irrelevant ones increases the chances of junk results being included in the search
At step 4 the tool fetches interoperable words related to your idea disclosure. One can select synonyms related to their idea. This step eliminates the difference of perception as it allows you to cover those concepts which are similar to your idea.
The system is able to fetch technical variations as it is integrated with the XLSCOUT corpus. The tool understands the idea of the disclosure using Natural language processing and applies machine learning algorithms to predict interoperable words.
It will take 10-15minute to shortlist the results. Total time depends on your input and variations which will take time accordingly. During this time period tool scan patent sets with keeping title and disclosure in scope and also variations and key features which are entered.
Results are ranked by matching input data with relevant patents. Patents with higher relevancy are ranked high in the list.
Family members of the respective patents can be seen in the main window. If not then you can select from display option.
The visualization tool applies intelligence to the obtained result set and generates graphs for concepts and assignees. Visualization tool applies intelligence to the result set obtained through the search and generates graphs to help you gain insights into your invention. This tool enables you to deep dive in and view and examine patents to a particular concept or assignee.
Yes, one can generate a report for specific patents related to the particular concept(s) or particular assignee(s) through the visualization tool. There are 3 graphs in the visualization tool. These graphs are dynamic. First graph: The second graph is that of technical categorization which outlines major concepts and subconcepts Second graph: Assignee Vs Technical Categorization - outlines major assignees and the technical concepts they are filling in.
Ideation tool gives you an indicator of parameters like idea strength, idea grant ratio, and idea demographics. The ideation tool also suggests inventive concepts which can be used to improvise the existing idea.
Idea strength is calculated by determining the overlap between existing prior art and the idea disclosure entered. If overlap found is less than idea strength is rated as strong and if overlap found is more and considerable then idea strength is rated as weak
Key feature analysis feature can be used to determine the number of patents talking about a single key feature or a combination of key features.
Machine suggested inventive concepts are the concepts suggested by the machine which it thinks is relevant and can be combined with the existing idea in order to improve the idea.
Through the generate report tab on the result screen. The generate report function enables you to document the search conducted. The report can be generated by size e.g top 10 or top 5 patents, by custom patent numbers, or for a range of patent numbers.
The report obtained through novelty checker is comprehensive enough for a first pass analysis and can be used for documenting the search for later time analysis. However, this report can’t be compared to a manual patentability report as the latter one is quite exhaustive and needs deep diving and more scrutiny of the prior art.
The report obtained included patent citations along with a key feature similarity score. It also includes NPL and all the input you gave to the machine
Yes if you conduct a re-search by using the “re-search tab”, it will be counted as a separate search
No, the system does not save the information from the previous search. Only idea title and disclosure are retained else all other input information is deleted.
You can either document your search by downloading a report or you can save the search if needed. You can just click on the “save search” tab to save your search. Doing so will make the search available in your history.
Ideacue is a module made to assist innovators and inventors. It is based on the principle of cause and effect analysis diagram or the Ishikawa diagram, also called as fish bone diagram. The module works by taking problem statement input and causes input from the user. It basically works on the Principles of Systematic Innovation Hence the ideacue module provides triggers for solutions to the problems by exploring parallel domains. Besides it also provides patent and publication prior art related to the problem statement entered that can further assist innovators in innovating.
Once the user enters the ideacue module, the very first screen is fishbone structure.
Step 1: Entering the problem statement and causesThe user need to enter a problem statement at the head section and then subsequent causes and subcauses. Minimum one cause and one subcause is necessary to use ideacue. Maximum of 6 causes and 3 subcauses for each can be added in the present version. The problem statement must define the problem being faced. Next causes should be entered which constitute towards that problem. Sub causes should be that information which drives that particular cause. Once the user has entered the problem statement and cause, click on next.
Step 2: Choosing technical ContradictionsThe second step asks for selecting technical contradictions. In this section the user needs to select a parameter they wish to improve and a parameter that they wish to conserve.
Step 3: Key Feature starmarking:In this step the tool breaks down the problem statement and causes as key features. This breakdown allows the users to star mark particular key features. Star Marking key features directs the tool to put special emphasis on that part of the problem statement or cause. This step is beneficial to get relevant patents and publication prior art.
Step 4: Selection of technology areas and classifications.At this step the user needs to select the technology domains of relevance. It will be on the basis of these technology domains that the tool will provide triggers. The user can also include some relevant classification in their search at this step. This is beneficial for improved quality of patent prior art.
Step 5: Selection of KeywordsFetched by XLSCOUT, this step enables users to select technical variations and key concepts. Again beneficial for patent and publication prior art results.
Ideacue gives three result outcomes for the search done. Patent Landscaper Based Results Patent prior art is fetched. Based on problem statements, key feature starmarking, classification selection and keyword selection. Gives a graphical representation which outlines major concepts and also classifies publications as per the concepts. Publication Landscaper Based Results. Relevant publication prior art is fetched. Based on problem statements, key feature starmarking, classification selection and keyword selection. Gives a graphical representation which outlines major concepts and also classifies publications as per the concepts. Ideation Based Results. Idea Cues are provided. Along with it technology triggers for each cue and selected technology domain. Custom ideation map also provided.
These are technical contradiction parameters that the user wants to improve in the problem statement. This is an important step as ideation based results depend largely on this step.
The data for relevant publications is fetched from google scholar. Ideacue is equipped with APIs to google scholar and hence searches in real time.
These are technical contradiction parameters that the user wants to improve in the problem statement. This is an important step as ideation based results depend largely on this step.
he data for relevant publications is fetched from google scholar. Ideacue is equipped with APIs to google scholar and hence searches in real time.
Yes, it is necessary to select atleast one technology domain in step 3. This is important as the tool will fetch unique and relevant technology domains as per the technology domains selected. The technology triggers will be unique to each technology domain.
Technology triggers are suggestions given by the tool which can assist in solving the problem statement. They are provided with an intent to trigger parallel thinking. Exploring around these triggers can help in improvising an idea or assist in solving a problem.
Yes XLSCOUT enables users to get patent alerts as per desired frequency. This is provided via the XLSCOUT SDI. It is a one-time setup and provides access controls.
Email patent alerts can be set up via XLSCOUT SDI. Email alerts are optional. Besides email alerts, the patent alerts get accumulated in a searchable repository. A dynamic patent alert dashboard is provided which assists in doing graphical analysis.
XLSCOUT SDI is equipped with a proprietary noise filtering algorithm that reduces false positives in patent alerts.
XLSCOUT supports two tools namely Company Explorer and Techscaper for landscape analysis. Company Explorer and Techscaper both are equipped with advanced NLP technologies like that of BERT to provide users with NLP-enriched competitive and technology landscapes respectively.
XLSCOUT is equipped with advanced NLP technology BERT which enables contextual analysis. NLP enriched landscapes are provided both by Techscaper and Company Explorer wherein they provide technology and Company Landscape respectively. The Landscape analysis provided henceforth enables users to auto categorize patents in technology categories. The categorization is done by automated taxonomy and also on the basis of custom taxonomy.
Landscape analysis is provided in the form of dynamic competitive and technology dashboards. These dashboards provide graphical analysis and filtering mechanisms. Within these dashboards, automatic clustering of patents is also provided. Clustering is done by automated taxonomy however the dashboard also gives users the freedom to create manual taxonomy and then hence direct the tool to cluster patents accordingly. This functionality is provided by both Company Explorer and Techscaper.
A competitive dashboard is obtained when a landscape analysis is done for more than one company on the company explorer. The competitive dashboard is made for more than one company. Assists in comparison. Can be irrespective of a technology domain or can be limited to a technology domain. Features offered by Competetive analytics dashboard. few features.
- Graphical analysis
- Making of CustomTaxonomy
A technological dashboard is obtained when a landscape study is done via the Techscaper tool. The graphs obtained are technology-oriented. This dashboard can help assist in identifying insights for patent data within a technology domain. The technology dashboard offers quite a few features.
- Graphical analysis
- Making of CustomTaxonomy
Automated taxonomy is the taxonomy made by the tool using NLP BERT technology. The tool applies intelligence and makes automated technology concepts and clusters patents according to tp the taxonomy hence made.
Manual taxonomy can be created through the intelligent dashboard available in both company explorer and tech scraper. It can be made through the technology breakdown section within the intelligent dashboard. Multilevel taxonomy can be created i.e Concepts and subconcepts can be made. This can enable very narrow and focused patent clustering.
Both Company Scraper and Techscaper allow filtering of patents. This again can be done via the intelligent dashboard. Filtering can be done through the following criteria
- Year(Publication, application, earliest priority year)
- legal status
- Patent Type
- Taxonomy (Automated, Custom)
To conduct a competitive analysis via the Company Explorer tool, enter more than one company.
A landscape analysis can be done via two ways through the Company Explorer tool. Simple Search: Just enter the company name. Either conduct a Landscape study on the whole company or with respect to a technology domain by entering technology concepts. To conduct a competitive landscape, enter more than one company. Advanced Search: Enter information in the fields provided under the advanced search menu.
Like Company Explorer, landscape analysis can be done via the same two ways i.e Simple search and advanced search. Simple Search: Just enter the technology domain of interest. Choose a date range and date criteria.
Advanced search is a fielded search wherein the user can enter information in the fields. It is provided with an aim to provide a close to query-based analysis experience but in a simplified way.
Assignee clusters are templates wherein assignees or companies can be grouped together to make them function as one group
Making assignee clusters eliminates the need to group assignees every time a user conducts a search on the same group of assignees.
Invalidator tool enables you to conduct a quick invalidation search. One can conduct an invalidation search by just entering the patent number.
There are two ways to conduct a search i.e by either proceeding to results directly or by supervising the search. Supervising the search enables you to direct the tool to give a much more refined result set.
In the main window, the first text field is to add a patent number. For reference, there is a random patent number added in the background. You can also refer to Google Patents to find relevant patent numbers according to your search.
Advanced search parameters enable you to refine your search in order to make it more focused. These parameters give you an option to enter a date range, focused keyword similar patents, etc.
Yes published patent applications can be searched through an invalidator.
The tool lists out all the claims of the patent number entered. You can select the claim(s) of your interest against which you want to find the prior art.
The tool breaks down the claim(s) selected in step 2 into key features. This breakdown of the claims into key features enables you to direct the tool to focus on particular key features. At this step the tool also applies NLP technology in order to understand the contextual meaning of the claims.
At step 4 the tool fetches interoperable words related to your idea disclosure. One can select synonyms related to their idea. This step eliminates the difference of perception as it allows you to cover those concepts which are similar to the idea disclosed in the patent number entered.
The reading bot is an NLU based bot that gives you a key feature mapping for each patent and facilitates reading patents quickly.
Yes, the tool covers NPL.
The whole web is the source of NPL. Once you conduct a search, the tool does a web search in real-time. Further, we also have API access to websites like a binge, IEEE, Scopus, Springer, PubMed, etc.
Yes, users can filter the NPL results by their source. Click on the “refine” tab at the upper right corner in order to view sources and filter accordingly.
The visualization tool applies intelligence to the obtained result set and generates graphs for concepts and assignees. This tool enables you to deep dive in and views and examine patents.
Yes, one can get a report for particular results as well. You can get a report for patents belonging to a particular assignee or for patents falling under a particular concept. Such a report can be generated through the visualization tool. Just click on the concept/ assignee you want the report for. Clicking on a particular assignee/concept.key-feature(s) will filter and list corresponding patents on the right-hand side. Click on generate report tab to get a report for those patents only.
Just like a novelty report, the invalidation report also covers patent citations, NPL, inputs given to the system, and key feature mapping.
XLSCOUT Expert search is a module that helps users conduct a search conventionally but with the convenience of fielded search. A user can input relevant information in the fields, increase or decrease the number of fields as per search need.
A user can add multiple search fields. The user can also customely set the nature of these fields. Following information can be set through the fields. Text : To choose the segment from wherein you want the keywords to be searched at.
- Full Text
- Title or Abstract
- Title, Abstracts or Claims
In the Expert search module, click on the tab with the attribute “Authorities/collection”. This tab can be located just below the Advanced search tab. It is from here that a user can select or unselect countries and jurisdictions. From this tab, the user can also select the required legal status.
A classification search enables users to conduct a search by a classification. A classification search can be conducted by selecting the classification field from the drop down menu. On hovering to the classification option, the user will be able to select the type of classification required. Classification models available which a user can select are:
- Classification IPC/CPC
- Classification CPC
- Classification IPC
- Classification UPC
- Classification F Term
When a user enters classification as a field and if the type of classification model is any from the IP/CPC model, CPC model and IPC model, then the system provides a tab for classification helper. Clicking on this tab enables the users to directly select the classifications of interest. IPC and CPC classifications are already pre integrated with XLSCOUT modules, hence the user can directly select from there.
- Selection of Classification IPC/CPC will prompt IPC/CPC helper tab
- Selection of Classification CPC will prompt CPC helper tab
- Selection of Classification IPC will prompt IPC helper tab
Yes XLSCOUT Expert Search allows users to limit a search by an assignee or an inventor. Just hover to the Names option from the dropdown menu. On hovering the user will get the Names menu. The user can either select the relevant assignee criteria or select the inventor option for the search. Assignee options available with the tool are:
- All Assignee
- Original Assignee
- Original Assignee Standardized
- Current Assignee
- Current Assignee Standardized
If the user has limited a search by an assignee but if the tool still shows other assignees in that search, this happens when the entered assignee is a co-assignee with another company or entity. In this case the co-assignee is also showcased by the tool that's why users might notice other assignees in their search results.
The corporate tree tab allows users to include subsidiaries of a particular assignee in the search.
Simple Legal Status --- gives patent publication's active /inactive status Legal State-- gives the legal state based on which the simple legal status (alive/dead/pending) is determined Eg. If simple status is Dead ---legal state could be expired or revoked or non-payment
Result list and filtering options The result screen of the expert search module lists patent results as per the query input. Besides a result list, the tool enables users to filter patents. Filtering options are given on the left hand side. Result analysis From this screen the user can also analyse the results on clicking on the analyze button at the bottom. Analyze button redirects to another screen which asks the user to choose from Technology Intelligence or Company Intelligence. Technology Intelligence will provide analysis on the basis of technology. Company intelligence will provide analysis on the basis of an assignee. Save search. The user can save their search. The tab is provided at the bottom of the screen in the red segment. Adjacent to the analyze button. Export The user can export patent results from a search to their local system.
Yes, a user can combine two or more individual searches by combining search queries. Goto the history page from the history tab. It will list out all the searches done until that moment of time. The system provides an ID no. to each search conducted. There is an input box given at the top. The user can enter the ID no. of each search query they want to combine. The user can apply logic operators to combine two or more than two search queries.
All main operators can be used to conduct a search on XL SCOUT Expert Search. Logical, Proximity, Wildcard and other operators can be used. To know about the esact operators, kindly click on the tab search guide there on the expert search dashboard.