Person validation and entity resolution conference speaker. Collective entity resolution in familial networks p kouki, j pujara, c marcum, l koehly, l getoor 2017 ieee international conference on data mining icdm, 227236, 2017. To reduce the typically high execution times, we investigate how learningbased entity resolution can be realized in a cloud infrastructure using mapreduce. Netowl entitymatcher provides accurate, fast, and scalable identity resolution based not only on similarities of the entity names but also other key entity attributes such as date of birth, place of birth, address, and nationality. The puzzle of entity resolution, where duplicate records are resolved and merged together in order to identify a specific entity of a person, place, or a thing, is a common challenge in the business world. A latent dirichlet model for unsupervised entity resolution indrajit bhattacharya lise getoor department of computer science university of maryland, college park, md 20742 abstract entity resolution has received considerable attention in recent years. Her current work includes research on link mining, statistical relational learning and representing uncertainty in structured and semistructured data. A primer on entity resolution by benjamin bengfort. Lise getoor is a professor in the computer science department, at the university of california, santa cruz. Nov 17, 2009 lise getoor is an associate professor in the computer science department at the university of maryland, college park. Entity resolution for big data lise getoor university of maryland, college park ashwin machanavajjhala duke university abstract entity resolution er, the problem of extracting, matching and resolving entity mentions in structured and unstructured data, is a longstanding challenge in database management, information.
Oyster open system entity resolution is an entity resolution system that supports probabilistic direct matching, transitive linking, and asserted. Record linkage rl is the task of finding records in a data set that refer to the same entity across different data sources e. The entity resolution control panel appears on the right. Machine learning, reasoning under uncertainty, databases, data science for social good, artificial intelligence, data integration, database query optimization and approximate query processing, entity resolution, information extraction, utility elicitation, planning under uncertainty, contraintbased reasoning, abstraction and problem reformulation. Ieee international conference on data mining icdm 2017. It helps solve different problems resulting from data entry errors, aliases, information silos and other issues where redundant data may cause confusion. Learningbased approaches show high effectiveness at the expense of poor efficiency. Carnegie mellon university, pittsburgh, pa fall 2014 visiting scholar, machine learning department, mentor. My advisor was lise getoor and i used to be part of the linqs lab. Among getoors crowning achievements is a datacleaning approach called graph identification that combines three techniques.
The link prediction work in the paper chapter4is based on relationship identi cation for social network discovery 48. A latent dirichlet model for unsupervised entity resolution authors. Entity resolution in the big data era avigdor gal technion israel institute of technology this is a short version of vldb2014 presentation. Getoor and her students have developed new algorithms that make use of relational information and other contextual information to improve the accuracy of entity resolution. Popular named entity resolution software cross validated. Collective entity resolution in relational data indrajit bhattacharya and lise getoor university of maryland, college park many databases contain uncertain and imprecise references to realworld. View colleagues of lise getoor ashwin machanavajjhala. Lise getoor, professor, computer science, uc santa cruz at. We pose typed entity resolution in relational data as a clustering problem and present experimental results on real data showing improvements over attributebased models when relations are leveraged. A visual analytic tool and its evaluation, hyunmo kang, lise getoor, ben shneiderman, mustafa bilgicyand louis licameley, ieee transactions on visualization and computer graphics tvcg, volume 14.
Entity resolution er, the problem of extracting, matching and resolving entity mentions in structured and. Given many references to underlying entities, the goal is. Lise getoor, university of maryland, college park collective entity resolution lise getoor is an associate professor in the computer science department at the university of maryland, college park. All content in this area was uploaded by lise getoor. In recommender systems my focus is on hybrid recommendations, on explanations, and fairness. Lise getoor, professor, computer science, uc santa cruz at mlconf sf 1. Entity resolution for big data proceedings of the 19th acm sigkdd. The goal of entity resolution is to determine the mapping from database references to discovered realworld entities.
Resolution, recommendation, and explanation in richly structured social networks. Entity resolution is a crucial step for data quality and data integration. Ironically, entity resolution has many duplicate names identity. Bruce golden a 2opt based heuristic for the hierarchal traveling salesman problem. This is an important area of research as it could save many computation cycles and thus allow accurate information provided to the right people at the right time. We describe existing solutions, current challenges, and open research problems. The most related work include recent approaches developed by andrew mccallum, william cohen, bradley malin, lise getoor, lee giles, etc. My research interests are in recommender systems and entity resolution. Basics of entity resolution python libraries for data. Lise getoor research on streaming inference in probabilistic graphical models. She has a phd in computer science from stanford university.
In the literature there is a number of techniques for deduplication and entity resolution, outlined by getoor et. Entity resolution with markov logic parag singla pedro domingos department of computer science and engineering university of washington seattle, wa 981952350, u. Entity resolution er, the problem of extracting, matching and resolving entity mentions in structured and unstructured data, is a longstanding challenge in database management, information retrieval, machine learning, natural language processing and statistics. Basics of entity resolution with python and dedupe district. Specifically, references to different entities may cooccur. Iterative record linkage for cleaning and integration. Databases are at the core of commercial software applications, and are essential for any application that requires storing, updating or consulting volumes of data in an efficient way. In many domains, such as social networks and academic circles, the underlying entities exhibit strong ties to each other, and as a result, their references often cooccur in the data. In these cases, collective entity resolution, in which entities for cooccurring references are determined jointly rather than independently, can improve entity resolution accuracy. My general research interests are in machine learning, reasoning under uncertainty, databases and artificial intelligence.
Therefore it is exceptionally timely that last week at kdd 20, dr. Sunter district data labs provides data science consulting and corporate training services. Code for the paper entity resolution in familial networks pigi kouki, jay pujara, christopher marcum, laura koehly, lise getoor. Graph identification lise getoor university of maryland. Lise getoors website at university of maryland college park umd, department of computer science. Relational clustering for multitype entity resolution. Ashwin machanavajjhala a theory for record linkage by ivan p.
Lise getoor, ashwin machanavajjhala, entity resolution. Figure 6 from learningbased entity resolution with. She received her phd from stanford university in 2001. Entity resolution is becoming an important discipline in computer science and in big. Oyster open system entity resolution is an entity resolution system that supports probabilistic direct matching, transitive linking, and asserted linking. We propose similarity measures for clustering references taking into account the different relations that are observed among the typed references.
In entity resolution, my focus is on collective approaches performing in richlystructured social networks. This tutorial brings together perspectives on er from a variety of fields, including databases, machine learning, natural language processing and information retrieval, to provide, in one setting, a survey of a large body of work. M y general research interests are in machine learning, reasoning under uncertainty, databases and artificial intelligence. Collective entity resolution lise getoor, university of maryland, college park, and indrajit bhattacharya, iis bangalore abstract in many domains, entity resolution results can be enhanced by combining information about the entitys attributes, together with cooccurrence information about the entities. Data is multimodal, multirelational, spatiotemporal, multimedia 4.
Alignment, identi cation, and analysis gaia opensource software library which not only provides an implementation of c3 but also algorithms for various tasks in network data such as entity resolution, link prediction, collective classi cation, clustering, active learning, data generation, and analysis. An interactive tool for entity resolution in social. Entity resolution er, the problem of extracting, matching and resolving entity mentions in structured and unstructured data, is a longstanding challenge in artificial intelligence, statistics, information retrieval, and database management. One of the challenges in big data analytics lies in being able to reason. Two considerations when forming a data warehouse are data cleansing including entity resolution and with schema integration including record. Workshop objectives introduce entity resolution theory and tasks similarity scores and similarity vectors pairwise matching with the fellegi sunter algorithm clustering and blocking for deduplication final notes on entity resolution 3. Entity resolution for big data association for computing. The tasks that are associated with the entity resolution process may include. Pdf a survey of entity resolution and record linkage. Big graph data science lise getoor university of california, santa cruz sf mlconf november 14, 2014 2. Why use structures in machine learning by lise getoor at. Work in chapter5is based on a submission active surveying for querydriven collective classi cation. We discuss both the practical aspects and theoretical underpinnings of er.
There are various approaches and algorithms can be used for named entity resolution. Record linkage is necessary when joining different data sets based on entities that may or may not share a common identifier e. Entity resolution for big data by benjamin bengfort. Machanavajjhalaaaai 12 part 1 abstractproblemstatement. A latent dirichlet model for unsupervised entity resolution. A visual analytic tool and its evaluation, hyunmo kang, lise getoor, ben shneiderman, mustafa bilgicyand louis licameley, ieee transactions on visualization and computer graphics tvcg, volume 14, number 5, 9991014, 2008. Collective entity resolution in relational data norc. Nov 21, 2014 lise getoor, professor, computer science, uc santa cruz at mlconf sf 1. Identity resolution can also be based on social network information such as employer, spouse, associate, etc. Mar 01, 2007 however, there is often additional relational information in the data. A visual analytic tool and its evaluation hyunmo kang, member, ieee computer society, lise getoor, member, ieee computer society, ben shneiderman, member, ieee computer society, mustafa bilgic, student member, ieee computer society, and louis licamele, student member, ieee computer society.
Visiting student, jack baskin school of engineering, mentor. I doubt that it is possible to determine precisely, what software belong to some of the most popular for solving that problem. Evaluation of entity resolution approached on real. Figure 6 from learningbased entity resolution with mapreduce. The entity resolution work in chapter3is based on the paper name reference resolution in organizational email archives 47. Aug 15, 20 a summary of the kdd 20 tutorial taught by dr. Early results for named entity recognition with conditional random fields, feature induction and webenhanced lexicons. Lp programs for max sat with approximation guarantees.
Traditional entity resolution approaches consider approximate matches between attributes of individual references, but this does not always work well. Collective entity resolution lise getoor, university of maryland, college park, and indrajit bhattacharya, iis bangalore abstract in many domains, entity resolution results can be enhanced by combining information about the entity s attributes, together with cooccurrence information about the entities. A great deal of research is focused on formation of a data warehouse. Two considerations when forming a data warehouse are data cleansing including entity resolution and with schema integration including record linkage.
Big questions in science 7 how can artificial intelligence. Mining for outliers in sequential databases authors. Entity resolution is the process by which a dataset is processed and records are identified that represent the same realworld entity. She has spent a lot of time studying machine learning, reasoning under uncertainty, databases, data science for social good, artificial intelligence. Engineering of large andor complex software systems. Why use structures in machine learning by lise getoor at nips. Dec 08, 2017 lise getoor is a professor in the computer science department, at the university of california, santa cruz. Kdd tutorial on entity resolution in big data umd department of. Lise getoor, member, ieee computer society, ben shneiderman, member, ieee computer society. The problem of named entity resolution is referred to as multiple terms, including deduplication and record linkage. Entity resolution is an operational intelligence process, typically powered by an entity resolution engine or middleware, whereby organizations can connect disparate data sources with a view to understanding possible entity matches and nonobvious relationships across multiple data silos.