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This document contains definitions of a wide range of concepts specific to and widely used within temporal databases. In addition to providing definitions, the document also includes separate explanations of many of the defined concepts. Two sets of criteria are included. First, all included concepts were required to satisfy four relevance criteria, and, second, the naming of the concepts was resolved using a set of evaluation criteria. The concepts are grouped into three categories: concepts of general database interest, of temporal database interest, and of specialized interest. This document is a digest of a full version of the glossary 1 . In addition to the material included here, the full version includes substantial discussions of the naming of the concepts.The consensus effort that lead to this glossary was initiated in Early 1992. Earlier status documents appeared in March 1993 and December 1992 and included terms proposed after an initial glossary appeared in SIGMOD Record in September 1992. The present glossary subsumes all the previous documents. It was most recently discussed at the "ARPA/NSF International Workshop on an Infrastructure for Temporal Databases," in Arlington, TX, June 1993, and is recommended by a significant part of the temporal database community. The glossary meets a need for creating a higher degree of consensus on the definition and naming of temporal database concepts.

We present an efficient algorithm (UWEP) for updating large itemsets when new transactions are added to the set of old transactions. UWEP employs a dynamic lookahead strategy in updating the existing large itemsets by detecting and removing those that will no longer remain large after the contribution of the new set of transactions. It differs from the other update algorithms by scanning the existing database at most once and the new database exactly once. Moreover, it generates and counts the minimum number of candidates in the new database. The experiments on synthetic data show that UWEP outperforms the existing algorithms in terms of the candidates generated and counted.

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