Entity resolution (ER), or deduplication is a computationally hard problem with O(n) time complexity. We reformulate ER as a search problem, and develop algorithms using efficient indices. Indices can enhance algorithm scalability, facilitate distributed processing, but require additional storage space. We study the performance and tradeoffs between index update and search in ER algorithms, and...

Entity Resolution is among the hottest topics in the field of Big data. It finds duplicates in datasets, which actually belong to same entity in the real world. Algorithms that perform Entity Resolution are computation intensive and consume a lot of time especially for large datasets. A lot of research has been conducted for improving Entity Resolution solutions. A number of algorithms are deve...

Chemical Named Entity Recognition (NER) is the basic step for consequent information extraction tasks such as named entity resolution, drug-drug interaction discovery, extraction of the names of the molecules and their properties. Improvement in the performance of such systems may affects the quality of the subsequent tasks. Chemical text from which data for named entity recognition is extracte...

One significant challenge to scaling entity resolution algorithms to massive datasets is understanding how performance changes after moving beyond the realm of small, manually labeled reference datasets. Unlike traditional machine learning tasks, when an entity resolution algorithm performs well on small holdout datasets, there is no guarantee this performance holds on larger hold-out datasets....

Entity resolution (ER) is the process of linking records that refer to same entity. Traditionally, this compares attribute values calculate similarities and then classifies pairs as referring entity or not based on these similarities. Recently developed graph-based ER approaches combine relationships between with improve linkage quality. Most only consider databases containing basic entities ha...

Abstract Entity Resolution is a technique to find similar records that may refer the same entity from one or many resources. It mainly used in data integration cleaning with existence of Big Data. not only helps organisations have clean data, but it also provides unified view their for later analysis. However, there no solution fitting all duplication issues. Because fact itself heterogeneous a...