In temporal document databases and temporal XML databases, temporal text-containment queries are a potential performance bottleneck. In this paper we describe how to manage documents and index structures in such databases in a way that makes temporal textcontainment querying feasible. We describe and discuss different index structures that can improve such queries. Three of the alternatives have been implemented in the V2 temporal document database system, and the performance of the index structures is studied using temporal web data. The results show that even a very simple time-indexing approach can reduce query cost by up to three orders of magnitude.

Storage costs are rapidly decreasing, making it feasible to store larger amounts of data in databases. This also makes it possible to store previous versions of data in the databases, instead of only keeping the last version. Recently, the amount of data available in XML has been rapidly increasing. In this paper, we describe TeXOR, a temporal XML database system built on top of an object-relational database system. We describe the TXSQL query language used in TeXOR for querying temporal XML documents stored in the system, discuss storage alternatives for XML documents in such a system, and some details about the implementation of the current TeXOR prototype.

Support for temporal text-containment queries (query for all versions of documents that contained one or more particular words at a particular time t) is of interest in a number of contexts, including web archives, in a smaller scale temporal XML/web warehouses, and temporal document database systems in general. In the V2 temporal document database system we employ a combination of full-text indexes and variants of time indexes to perform efficient textcontainment queries. This approach was optimized for moderately large temporal document databases. However, for "extremely large databases" the index space usage of the approach could be too large. In this paper, we present a more spaceefficient solution to the problem, the architecture of the interval-based temporal text index (ITTX), we present appropriate algorithms for update and retrieval, and we discuss advantages and disadvantages of the two approaches.

In temporal document databases and temporal XML databases, temporal text-containment queries are a potential performance bottleneck. In this paper we describe how to manage documents and index structures in such databases in way that makes temporal text-containment querying feasible. We describe and discuss different index structures that can improve such queries. Three of the alternatives have been implemented into the V2 temporal document database system, and the performance of the index structures is studied using temporal web data. The results show that even a very simple time-indexing approach can reduce query cost by up to three orders of magnitude.

The Web has become the main publication medium worldwide, covering almost every facet of human activity. In many cases, the Web is the only medium where such information is recorded. However, the Web is an ephemeral medium whose contents are constantly changing and new information is rapidly replacing old information, and hence the critical importance of establishing web archives to capture at least partially the information that is deemed important in the long term. In this work, we address search and access strategies of web archives, and outline our approach for carrying out effective search and retrieval of archived web contents. In a typical web archive, the contents are highly unstructured and interlinked within a temporal context. Over time, such archived web contents can present an unprecedented opportunity for information and knowledge discovery in linking and fusing the appropriate information spread over several contextual domains, including the temporal domain. We present in this paper a number of methods for searching web archives which will significantly contribute towards realizing this opportunity. We also address different presentation strategies of the contents of interest, and extend information retrieval techniques to include temporal contexts seamlessly into the architecture.