## 1 Introduction: Name Disambiguation and Collocation  
Databases, search engines, and scholarly communication are increasingly paying attention to the need to accurately disambiguate the same or similar names in online databases. Large databases are beset by the problem of a single name being shared by two or more people, families, or organizations. This problem causes search results to be populated with unwanted documents, forcing the searcher to sort through the results and eliminate the unwanted items. Indeed, \"... in this day and age, it can be next to impossible to find all the papers written by a given scientific author\" [1]. Numerous efforts are currently underway to ameliorate the problem of a single name being used in a database to refer to more than one person or entity. This article describes the name disambiguation problem, describes different methods of achieving effective name disambiguation and reviews the major initiatives now taking place to achieve effective and consistent name disambiguation in online databases. Morespecifically, this paper looks at the role name metadata plays in disambiguating names in online databases.  
Additionally, the paper looks at a related problem, collocating in search results all the variant forms of a single person's, organization's or family's name. Collocation here means grouping together documents by or about a single name regardless of how the name appears in the documents in question. Information retrieval systems are challenged by the different forms a single person's name can take. For example the name _[PERSON]_ can also appear as _[PERSON]_ or as the initial \(W\). This paper will describe the many different forms a single name can take, the problems these variant forms cause for search engines, and how database search engines can use metadata to resolve the variant name problem.  
When a searcher searches for all the works of a particular author, ideally the search results should contain a complete set of only that author's works. In most current full-text search systems, this ideal is rarely achieved. Indeed, the problems associated with ambiguous names and variant forms of names are worsened when one searches across multiple domains and multiple databases. Algorithmic and deterministic use of name metadata are promising and increasingly-popular tools that can help search engines provide complete and precise results in searches that involve names.  
The name disambiguation problem and the variant name problem are examples of the homonym problem and the synonym problem [2] in full-text searching. The homonym problem occurs when the same word refers to two or more concepts, such as \"dating,\" which can refer to the social custom (going out on a date) or the process archaeologists use to determine an artifact's age (radiocarbon dating). The synonym problem occurs when more than one term represents a single concept, such as the pair _leprosy_, _[PERSON]'s disease_, which both mean the same thing. Because most current search engines work by matching terms in a search query with terms in online documents, both the synonym problem and the homonym problem yield search results that contain both unwanted and missed documents. In terms of searching names, search results contain items that include names that match the search query but that are for a different entity that only coincidentally shares the same name, or search results exclude documents that contain variant forms of the name that do not match the form used in the original search query.