Various exemplary systems and methods for linking entity references and identifying associations are presented. In particular, a method is provided for linking a plurality of entity references to at least one entity. The method comprises the steps of evaluating a probability of a match between a first entity reference and a second entity reference based at least in part on a statistical significance of one or more field values being common to both the first entity reference and the second entity reference, wherein field value statistical significance is inversely related to a number of field value occurrences occurring in some or all of the plurality of entity references and linking the first entity reference with the second entity reference when the probability is greater than or equal to a match threshold.

Method and system for processing and linking data records

Exemplary systems and methods for linking entity references to entities and identifying associations between entities are presented. In particular, a method for delinking one or more entity references linked to a same entity is provided, where the one or more entity references have at least one common data field. The method comprises the steps of evaluating at least one actual measurement of the entity based at least in part on one or more field values of the one or more entity references, determining a difference between the at least one actual measurement and at least one predefined measurement associated with the entity and delinking the one or more entity references based at least in part on a comparison of the difference and a defined threshold.

Method and system for linking and delinking data records

A method, program and system for processing data is disclosed. The data comprises identifiers of a plurality of entities. The method, program and system comprising the steps of: (a) receiving one or more records, each record having a plurality of identifiers, each record corresponding with at least one entity [20], (b) utilizing a cryptographic algorithm to process at least two of the plurality of identifiers in the record [48], (c) sometimes after transmitting the processed record to a separate system or database, comparing the processed record to previously stored data [54]; (d) matching the processed record with previously stored data that is determined to reflect the entity, the previously stored data that is determined to reflect the entity comprising at least a portion of at least two previously stored data that is determined to reflect the entity comprising at least a portion of at least two previously received records and/or based upon another identifier [54]; and/or (e) associating the processed record with previously stored data that is determined to reflect a relationship with the entity [54].

Confidential data sharing and anonymous entity resolution

Embodiments of the invention provide a system and method of automatically generating weights for matching data records. Each field of a record may be compared by an exact match and/or close matches and each comparison can result in a mathematical score which is the sum of the field comparisons. To sum up the field scores accurately, the automatic weight generation process comprises an iterative process. In one embodiment, initial weights are computed based upon unmatched-set probabilities and default discrepancy weights associated with attributes in the comparison algorithm. A bulk cross-match is performed across the records using the initial weights and a candidate matched set is computed for updating the discrepancy probabilities. New weights are computed based upon the unmatched probabilities and the updated discrepancy probabilities. Test for convergence between the new weights and the old weights. Repeat with the new weight table until the weights converge to their final value.

System and method for automatic weight generation for probabilistic matching

Embodiments disclosed herein are directed to systems and methods for enabling the matching of third party data with access providers' subscriber data in a privacy compliant manner, and then connecting an internet user to that third party data for use by marketers, content providers, or other interested parties in a manner that protects consumer privacy at all times. In one embodiment, an access provider such as an ISP sends its subscriber data to a double blind processor that generates an encrypted key for each subscriber. The key is then used to find matching consumer data, for example, consumer segments that represent previously collected or modeled consumer attitudinal, habit, or financial data. The key may be forwarded to a real time marketing bureau, which may use the matched data in subsequent real-time or substantially real-time operations to provide consumer or business data to advertisers, content providers, and other interested parties.

Systems and methods for providing real time anonymized marketing information

Apparatus and method for creating de-identified and linked records is described. More particularly, data records are de-identified at a client computer. De-identification includes field-level one-way encryption. De-identified records may then be sent to a server computer for linkage. Linkage is done using match codes created for such data records at the client computer. The server computer is configured to provide longitudinal linkage of de-identified client records to de-identified master records. In this manner, privacy may be maintained at the client computer prior to transmission of information, and longitudinal linkage of records may occur without exposing personally identifying information.

De-identification and linkage of data records

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Kathi Evans

Author Tools

Chat about Author

Papers

De-identification and linkage of data records