Learn How NumLookup Works
NumLookup started off as a Reverse Phone Lookup service in 2019. Over the years, based on user feedback, we have added additional tools such as People Search, Reverse Image Search and Plagiarism Checker to create an increasingly comprehensive Information Search platform. Because of the unique features and differences in the underlying technologies built to support these tools, we will go through each of them individually to help you understand how they work.
Online Phone Directory
NumLookup's is constantly updating its world's most extensive online phone directory that is accessible via any web browser. How it works is very simple: you give NumLookup a phone number, and NumLookup gives you the owner's information such as the full name, phone carrier information, social search by phone number, address, relatives information and more in return. Performing a phone number search has never been more easy.
Although the concept & functionality is very light-weight & simple - the inner workings of NumLookup are far from it. Our goal in this article is to briefly explain how NumLookup is able to quickly and accurately provide you with the full name for any phone in the world.
NumLookup is powered by a farm of geographically distributed servers that are always searching, collecting and processing publicly available telephone information from around the world. If there is any piece of phone number related information available out there, our goal is to be able to find it and collect it. Our ability to successfuly do this provides us with a solid foundation to build a world-class reverse phone lookup tool on.
Once all the information is collected, our servers then start building or augmenting unique individual profiles. Our goal is to be able to create a virtual identifier for each and every person with zero overlaps or gaps. For example: If we find and collect 2 different phone numbers for the same full name that seemingly appear to be the same person, we use other personally identifiable information such as age, gender, address, etc. to conclude if the information found is for two different individuals that just happen to share the same name, or, if both phone numbers are owned by the same person.
This enables us to build a comprehensive telephone directory for the world. Keep in mind that all information that is found and collected by NumLookup is already publicly available. NumLookup is merely making this information easily available to you through an easy to use web application.
If you ever find yourself wondering who called you, you now know which tool to use. Remember, NumLookup is just a few clicks away!
At NumLookup, we are committed to providing efficient, comprehensive, and reliable Information Search services to our users. In our pursuit of continual advancement, we are proud to introduce the beta version of our 'People Search' feature. The process begins with you entering some basic information about the person you are looking for. This includes the person's full name and the state of residence. We plan to add more search options in the future - the idea being that the more specific information you can enter, the better the results will be. Once the data is entered by you, our system begins to collect information from a range of databases and sources. These might include public records, social media profiles, professional listings, and more. Our tool is designed to respect user privacy and adheres strictly to legal guidelines when sourcing information. Since this feature is currently in beta, the results are not guaranteed to be entirely accurate. We thank you for your patience and feedback while we continue to enhance this feature.
Reverse Image Search
Our Reverse image search technology is a sophisticated system that can locate similar and exact matches of an image across the entire internet. Here's how it works:
- Image Upload
The first step is to provide an image for the search. This can be done by uploading the image directly from your device.
- Feature Extraction
Once the image is uploaded, NumLookup uses computer vision techniques to extract features from the image. These can be colors, shapes, textures, or other distinctive elements. This process is often achieved through methods such as Scale-Invariant Feature Transform (SIFT), Speeded Up Robust Features (SURF), or ORB (Oriented FAST and Rotated BRIEF), among others.
- Image Fingerprinting or Hashing
The extracted features are then used to create a unique identifier for the image, often referred to as an image's fingerprint or hash. This process helps to reduce the image's data footprint while retaining its unique aspects for comparison. The hashing algorithm is designed in a way that even slight modifications to the image do not drastically change the hash value.
- Image Database Search
Next, this unique fingerprint is compared against a vast database of images that have been similarly processed. This is where the real 'search' happens. NumLookup scans its database, containing data on more than 10 billion images, looking for images with matching or closely similar fingerprints.
- Machine Learning and AI
Advanced systems often incorporate machine learning and AI algorithms that help in understanding the context and content of the image. They are continuously trained to recognize specific patterns or objects in images, which aids in finding more contextually accurate matches.
- Result Ranking and Display
After the search, the system ranks the results based on their similarity to the input image. The user is then presented with a list of images that closely match or are similar to the original image, often along with the source where the image is located.
Our Reverse Image Search is a truly powerful tool with numerous applications, including finding the original source of an image, locating higher resolution versions, identifying objects or people within the image, and detecting instances of copyright infringement.
Our Plagiarism Checker is an incredibly complex tool that uses several technologies to function. Lets dive straight into explaining how it works:
- Document Upload and Parsing
The first step involves uploading a document into the system. NumLookup accepts a range of formats like .doc, .docx, .pdf, .txt, and more. Upon receiving a document, the system parses it to extract the text. Depending on the file type, different parsing algorithms can be employed. For instance, PDF files may require Optical Character Recognition (OCR) to convert images of text into machine-readable text.
- Text Fragmentation
After the text has been extracted, it's broken down into smaller units, usually phrases or sentences, to be processed. This step is critical as it allows the checker to look for similarities at a sub-sentence (granular) level of detail.
- Database Lookup
The next step involves comparing each fragment to a comprehensive and ever-expanding database that contains a multitude of sources. These databases (what we call our magic pot!) include published articles, web pages, academic papers, books, and other and all digital content. The scale of these databases spans billions of documents.
- Matching Algorithm
This is where our sophisticated algorithms come into play. NumLookup uses complex matching algorithms to cross-reference each text fragment against the items in the database. We employ techniques from information retrieval and natural language processing, such as fingerprinting, string matching, and cosine similarity, to look for exact and near-exact matches.
- Report Generation
Finally, the system generates a report detailing any detected similarities. The report includes the percentage of the text that is similar to existing sources, the source of the matched text, and sometimes a direct comparison highlighting the similar sections. The report at this time is not able to distinguish between properly cited and uncited matches - something we plan to add soon to provide a more accurate view of potential plagiarism.