In these cases, collective entity resolution, in which entities for cooccurring references are determined jointly rather than independently, can improve entity resolution accuracy. Person validation and entity resolution conference speaker. Therefore it is exceptionally timely that last week at kdd 20, dr. Iterative record linkage for cleaning and integration. Ashwin machanavajjhala a theory for record linkage by ivan p. The goal of entity resolution is to determine the mapping from database references to discovered realworld entities. My advisor was lise getoor and i used to be part of the linqs lab. Specifically, references to different entities may cooccur. Lise getoors website at university of maryland college park umd, department of computer science. 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. Record linkage is necessary when joining different data sets based on entities that may or may not share a common identifier e. Nov 21, 2014 lise getoor, professor, computer science, uc santa cruz at mlconf sf 1. Ieee international conference on data mining icdm 2017. Popular named entity resolution software cross validated.
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. Resolution, recommendation, and explanation in richly structured social networks. 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. Oyster open system entity resolution is an entity resolution system that supports probabilistic direct matching, transitive linking, and asserted.
Basics of entity resolution python libraries for data. Entity resolution er, the problem of extracting, matching and resolving entity mentions in structured and. Bruce golden a 2opt based heuristic for the hierarchal traveling salesman problem. The link prediction work in the paper chapter4is based on relationship identi cation for social network discovery 48. 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. My research interests are in recommender systems and entity resolution. 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. Two considerations when forming a data warehouse are data cleansing including entity resolution and with schema integration including record. Oyster open system entity resolution is an entity resolution system that supports probabilistic direct matching, transitive linking, and asserted linking. Entity resolution for big data association for computing.
Big questions in science 7 how can artificial intelligence. 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. Graph identification lise getoor university of maryland. 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. 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. We propose similarity measures for clustering references taking into account the different relations that are observed among the typed references. Early results for named entity recognition with conditional random fields, feature induction and webenhanced lexicons. A latent dirichlet model for unsupervised entity resolution. Her current work includes research on link mining, statistical relational learning and representing uncertainty in structured and semistructured data. Figure 6 from learningbased entity resolution with. The tasks that are associated with the entity resolution process may include. 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.
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. Basics of entity resolution with python and dedupe district. 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. All content in this area was uploaded by lise getoor.
Lise getoor is a professor in the computer science department, at the university of california, santa cruz. 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. Visiting student, jack baskin school of engineering, mentor. Lise getoor, ashwin machanavajjhala, entity resolution. 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. Lp programs for max sat with approximation guarantees. We describe existing solutions, current challenges, and open research problems. The entity resolution work in chapter3is based on the paper name reference resolution in organizational email archives 47.
Identity resolution can also be based on social network information such as employer, spouse, associate, etc. There are various approaches and algorithms can be used for named entity resolution. Traditional entity resolution approaches consider approximate matches between attributes of individual references, but this does not always work well. In entity resolution, my focus is on collective approaches performing in richlystructured social networks.
Record linkage rl is the task of finding records in a data set that refer to the same entity across different data sources e. Entity resolution is becoming an important discipline in computer science and in big. Figure 6 from learningbased entity resolution with mapreduce. In the literature there is a number of techniques for deduplication and entity resolution, outlined by getoor et. The most related work include recent approaches developed by andrew mccallum, william cohen, bradley malin, lise getoor, lee giles, etc. Carnegie mellon university, pittsburgh, pa fall 2014 visiting scholar, machine learning department, mentor. Relational clustering for multitype entity resolution. Engineering of large andor complex software systems. Dec 08, 2017 lise getoor is a professor in the computer science department, at the university of california, santa cruz. She has a phd in computer science from stanford university.
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. We discuss both the practical aspects and theoretical underpinnings of er. The problem of named entity resolution is referred to as multiple terms, including deduplication and record linkage. Machanavajjhalaaaai 12 part 1 abstractproblemstatement. In recommender systems my focus is on hybrid recommendations, on explanations, and fairness. To reduce the typically high execution times, we investigate how learningbased entity resolution can be realized in a cloud infrastructure using mapreduce. 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. 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. Indrajit bhattacharya, lise getoor, querytime entity resolution, journal of artificial intelligence research, v.
Lise getoor, professor, computer science, uc santa cruz at mlconf sf 1. Lise getoor is an associate professor in the computer science department at the university of maryland, college park. Big graph data science lise getoor university of california, santa cruz sf mlconf november 14, 2014 2. Two considerations when forming a data warehouse are data cleansing including entity resolution and with schema integration including record linkage. Entity resolution for big data proceedings of the 19th acm sigkdd. The entity resolution control panel appears on the right.
A latent dirichlet model for unsupervised entity resolution authors. With fellow researchers at the universitys humancomputer interaction laboratory, getoor developed ddupe, a tool for eliminating data duplication that is available as. My general research interests are in machine learning, reasoning under uncertainty, databases and artificial intelligence. One of the challenges in big data analytics lies in being able to reason. Collective entity resolution in relational data norc. A primer on entity resolution by benjamin bengfort. Pdf a survey of entity resolution and record linkage. Mining for outliers in sequential databases authors. Lise getoor, member, ieee computer society, ben shneiderman, member, ieee computer society. Why use structures in machine learning by lise getoor at. Entity resolution with markov logic parag singla pedro domingos department of computer science and engineering university of washington seattle, wa 981952350, u. Lise getoor, professor, computer science, uc santa cruz at.
It helps solve different problems resulting from data entry errors, aliases, information silos and other issues where redundant data may cause confusion. 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. Nov 17, 2009 lise getoor is an associate professor in the computer science department at the university of maryland, college park. Lise getoor research on streaming inference in probabilistic graphical models. Data is multimodal, multirelational, spatiotemporal, multimedia 4. 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. 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. 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. I doubt that it is possible to determine precisely, what software belong to some of the most popular for solving that problem.
Aug 15, 20 a summary of the kdd 20 tutorial taught by dr. Kdd tutorial on entity resolution in big data umd department of. A great deal of research is focused on formation of a data warehouse. Mar 01, 2007 however, there is often additional relational information in the data. Learningbased approaches show high effectiveness at the expense of poor efficiency. Entity resolution in the big data era avigdor gal technion israel institute of technology this is a short version of vldb2014 presentation. She has spent a lot of time studying machine learning, reasoning under uncertainty, databases, data science for social good, artificial intelligence. An interactive tool for entity resolution in social. 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. View colleagues of lise getoor ashwin machanavajjhala. Why use structures in machine learning by lise getoor at nips. 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.
Entity resolution is the process by which a dataset is processed and records are identified that represent the same realworld entity. Entity resolution for big data by benjamin bengfort. M y general research interests are in machine learning, reasoning under uncertainty, databases and artificial intelligence. Evaluation of entity resolution approached on real. Work in chapter5is based on a submission active surveying for querydriven collective classi cation. Ironically, entity resolution has many duplicate names identity. Given many references to underlying entities, the goal is.
Among getoors crowning achievements is a datacleaning approach called graph identification that combines three techniques. Code for the paper entity resolution in familial networks pigi kouki, jay pujara, christopher marcum, laura koehly, lise getoor. She received her phd from stanford university in 2001. Entity resolution is a crucial step for data quality and data integration.
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