Abstract: We analyze the "query by committee" algorithm, a method for filtering informative queries from a random stream of inputs. We show that if the two-member committee algorithm achieves information gain with positive lower bound, then the prediction error decreases exponentially with the number of queries. We show that, in particular, this exponential decrease holds for query learning of thresholded smooth functions.

Abstract: ObjectStore is an object-oriented database system supporting persistence orthogonal to type, transaction management, and associative queries. Collections are provided as objects. The data model is non-1NF, as objects may have embedded collections. Queries are integrated with the host language in the form of query operators whose operands are a collection and a predicate. The predicate may itself contain a (nested) query operating on an embedded collection. Indexes on paths may be added and removed dynamically. Collections, being treated as objects, may be referred to indirectly, e.g., through a by-reference argument. For this reason and others, multiple execution strategies are generated, and a final selection is made just prior to query execution. Nested queries can result in interleaved execution and strategy selection.

Abstract: An information search terminal apparatus and information search system for performing information search by using a variety of windows assure high manipulatability for the user by making available information of the results of searches performed in the past and the current system state. The information search terminal and system includes a query statement input window for inputting a search query statement for a search term, a search history display window for displaying the search query statement and the number of documents as hit in the search, a search result list display window for displaying in juxtaposition a plurality of titles of documents as hit in the form of a list, and a document display window for displaying a document containing the search term and resulting from the search

Abstract: Cooperative query answering extends the classical notion of query answering to provide neighborhood and associated information Neighborhood query answering relaxes the query and its answer via abstract representations To integrate the abstraction view with the subsumption (is-a) and composition (part-of) views of type hierarchy, the notion of type abstraction hierarchy is introduced To evaluate and control query relaxation, a nearness measure mechanism is provided Associative query answering provides information conceptually related to, but not explicitly asked by the query As object association is context sensitive, a DB-Pattern-KB framework is developed that couples domain-specific knowledge and participating objects in localized problem domains via virtual database patterns Associative query answering can then be accomplished through tracing the behavior dependencies among cooperating objects in those problem domains Such a framework allows related databases and knowledge bases to be linked dynamically in various contexts yet be maintained relatively independent of each other The proposed approach has been implemented in the cooperative database system tested, CoBase, at UCLA Our experience reveals that the proposed techniques are effective for cooperative query answering

Abstract: We argue that those metaphors currently used for the design of user interfaces to databases and for visual query languages are not sufficient in the context of spatial information systems for they do not take advantage of the natural intuitive properties of spatial data. The paper proposes a new metaphor for handling spatial data, termed the blackboard metaphor, which overcomes these drawbacks. Based upon this paradigm a fully-fledged visual logic query language for spatial information systems called Sketch! is introduced. Its major advantage is that it facilitates a very intuitive, natural way to express spatial queries.

Abstract: This study compares a linear keyword language interface and a restricted natural language interface for data retrieval by a novice user. The comparison focuses on the effect of different data base interfaces on user performance as measured by query correctness and query writing time in a query writing task across varying query types and training levels. To accomplish this objective, a laboratory experiment was conducted using a split-plot factorial design using two between-subjects factors and one within-subjects factor. The results indicate that the restricted natural language subjects performed significantly better than the linear keyword language subjects in terms of both query correctness and query writing time.

Abstract: Research in temporal databases has mainly focused on defining temporal data models by extending existing models, and developing access structures for temporal data. Little has been done on temporal query processing and optimization. In this paper, we propose a uniform framework for processing temporal queries, which builds upon well-understood techniques for processing non-temporal queries. We start with an object-oriented model, and rely on its rich type system to model complex temporal information. The same query language is used to express temporal and non-temporal queries uniformly. A major benefit to this approach is that temporal query processing can be smoothly extended from an existing (non-temporal) query processing framework. For the purpose of query processing, we describe an object algebra, into which queries are compiled. Since the object algebra resembles the relational algebra, familiar relational query optimization techniques can be used. However, since the physical representation of temporal data and access methods differ from those of nontemporal data, new algorithms must be developed to evaluate the algebraic operators. We demonstrate that temporal queries can be processed and optimized under the existing query processing framework.

Abstract: It is well known that using conventional concurrency control techniques for obtaining serializable answers to long-running queries leads to an unacceptable drop in system performance. As a result, most current DBMSs execute such queries under a reduced degree of consistency, thus providing non-serializable answers. In this paper, we present a new and highly concurrent approach for processing large decision support queries in relational databases. In this new approach, called compensation-based query processing, concurrent updates to any data participating in a query are communicated to the query's on-line query processor, which then compensates for these updates so that the final answer reflects changes caused by the updates. Very high concurrency is achieved by locking data only briefly, while still delivering transaction-consistent answers to queries.

Abstract: A multidatabase system (MDBS) integrates information from autonomous local databases managed by heterogeneous database management systems (DBMS) in a distributed environment. For a query involving more than one database, global query optimization should be performed to achieve good overall system performance. The significant differences between an MDBS and a traditional distributed database system (DDBS) make query optimization in the former more challenging than in the latter. Challenges for query optimization in an MDBS are discussed in this paper. A two-phase optimization approach for processing a query in an MDBS is proposed. Several global query optimization techniques suitable for an MDBS, such as semantic query optimization, query optimization via probing queries, parametric query optimization and adaptive query optimization, are suggested. The architecture of a global query optimizer incorporating these techniques is designed.

Abstract: This thesis is aimed at investigating interactive query expansion within the context of a relevance feedback system that uses term weighting and ranking in searching online databases that are available through online vendors. Previous evaluations of relevance feedback systems have been made in laboratory conditions and not in a real operational environment. The research presented in this thesis followed the idea of testing probabilistic retrieval techniques in an operational environment. The overall aim of this research was to investigate the process of interactive query expansion (IQE) from various points of view including effectiveness. The INSPEC database, on both Data-Star and ESA-IRS, was searched online using CIRT, a front-end system that allows probabilistic term weighting, ranking and relevance feedback. The thesis is divided into three parts. Part I of the thesis covers background information and appropriate literature reviews with special emphasis on the relevance weighting theory (Binary Independence Model), the approaches to automatic and semi-automatic query expansion, the ZOOM facility of ESA/IRS and the CIRT front-end. Part II is comprised of three Pilot case studies. It introduces the idea of interactive query expansion and places it within the context of the weighted environment of CIRT. Each Pilot study looked at different aspects of the query expansion process by using a front-end. The Pilot studies were used to answer methodological questions and also research questions about the query expansion terms. The knowledge and experience that was gained from the Pilots was then applied to the methodology of the study proper (Part III). Part III discusses the Experiment and the evaluation of the six ranking algorithms. The Experiment was conducted under real operational conditions using a real system, real requests, and real interaction. Emphasis was placed on the characteristics of the interaction, especially on the selection of terms for query expansion. Data were collected from 25 searches. The data collection mechanisms included questionnaires, transaction logs, and relevance evaluations. The results of the Experiment are presented according to their treatment of query expansion as main results and other findings in Chapter 10. The main results discuss issues that relate directly to query expansion, retrieval effectiveness, the correspondence of the online-to-offline relevance judgements, and the performance of the w(p — q) ranking algorithm. Finally, a comparative evaluation of six ranking algorithms was performed. The yardstick for the evaluation was provided by the user relevance judgements on the lists of the candidate terms for query expansion. The evaluation focused on whether there are any similarities in the performance of the algorithms and how those algorithms with similar performance treat terms. This abstract refers only to the main conclusions drawn from the results of the Experiment: (1) One third of the terms presented in the list of candidate terms was on average identified by the users as potentially useful for query expansion; (2) These terms were mainly judged as either variant expression (synonyms) or alternative (related) terms to the initial query terms. However, a substantial portion of the selected terms were identified as representing new ideas. (3) The relationship of the 5 best terms chosen by the users for query expansion to the initial query terms was: (a) 34% have no relationship or other type of correspondence with a query term; (b) 66% of the query expansion terms have a relationship which makes the term: (bl) narrower term (70%), (b2) broader term (5%), (b3) related term (25%). (4) The results provide some evidence for the effectiveness of interactive query expansion. The initial search produced on average 3 highly relevant documents at a precision of 34%; the query expansion search produced on average 9 further highly relevant documents at slightly higher precision. (5) The results demonstrated the effectiveness of the w(p—q) algorithm, for the ranking of terms for query expansion, within the context of the Experiment. (6) The main results of the comparative evaluation of the six ranking algorithms, i.e. w(p — q), EMIM, F4, F4modifed, Porter and ZOOM, are that: (a) w(p — q) and EMIM performed best; and (b) the performance between w(p — q) and EMIM and between F4 and F4modified is very similar; (7) A new ranking algorithm is proposed as the result of the evaluation of the six algorithms. Finally, an investigation is by definition an exploratory study which generates hypotheses for future research. Recommendations and proposals for future research are given. The conclusions highlight the need for more research on weighted systems in operational environments, for a comparative evaluation of automatic vs interactive query expansion, and for user studies in searching weighted systems.

Abstract: The problem of time-constrained query evaluation in a single-user database management system (DBMS) is considered. CASE-DB is a real-time, single user, relational prototype DBMS that uses the relational algebra as its query language. Given a nonaggregate query and a fragment chain for each input relation of the query. CASE-DB uses iterative query evaluation techniques to obtain a response first to a modified version of the query, and then to successively improved versions of the query. CASE-DB controls the risk of overspending the time quota at each step using a risk control technique. For periodically occurring queries, CASE-DB uses incremental query evaluation techniques that make sure that each operator in the query has at least one operand relation which contains the changes in the last period, and is expected to be very small compared to the actual database relation. >

Abstract: Today's enterprises typically employ multiple information systems which are independently developed, locally administered and different in logical or physical designs. Therefore, a fundamental challenge in enterprise information management is the integration of such systems across functional boundaries within an organization. Conventional technologies, such as syntax-based query languages and heterogeneous distributed databases (HDDBMS) are not sufficient to solve this problem. This thesis develops a new approach, the model-assisted global query system, that utilizes enterprise metadata to facilitate global query formulation and processing. A definitive model that characterizes the various classes and roles of knowledge in terms of these metadata is presented. The significance of possessing this knowledge (via a metadatabase) for the notion of "on-line intelligence and assistance" is analyzed. Finally, the utilization of this new approach for major, difficult tasks in global query operations is established. Using this on-line knowledge, new methods are developed and verified using a prototype system to provide non-syntax-based global query capabilities to enterprise users. Specifically, these methods include (1) a model traversal method that allows direct articulation in terms of information models for global query formulation, (2) a knowledge processing method that detects and resolves conflicts using a rule processor, and (3) methods for global query optimization, implicit joins determination, and results integration. The model-assisted approach also resolves some interoperability issues (e.g., differences and incompatibilities among local systems) in information sharing. Traditional HDDBMS approaches handle these differences by imposing an integrated schema on the local systems. This approach, instead, shows that the same objective of resolving differences can be accomplished by utilizing the metadatabase containing data semantics, conversion rules, and other knowledge of the system. This way, not only difficult tasks such as schemata integration at both design time and run-time can be largely avoided, but also a higher degree of flexibility of system evolution can be achieved. The latter is an important goal of open system architecture. In sum, the Model-assisted Global Query System approach contributes to the problem of global queries in heterogeneous, distributed environments. The direct method in its own right also supports a high-level user interface (e.g., decision-support query formulation) without requiring technical details. This approach can be further generalized to facilitate other kinds of interoperability tasks in general software environments including distributed computing concurrent application systems, and other paradigms that involve interpretations and translations between the globally formulated structures and their local implementations.

Abstract: The authors describe a framework for query optimization for knowledge base management systems (KBMSs) based on the knowledge representation language Telos. The framework involves temporal and syntactic simplifications and semantic modification of the queries. Temporal simplification attempts to select parts of a knowledge base that are relevant to a query from a temporal viewpoint. Syntactic simplification exploits structural properties of the data model and attempts to transform the query into an equivalent and more efficient one. Semantic transformation uses knowledge specific to the application domain to transform a user-specified query into another form which gets the same answer and is processed efficiently. The three steps were integrated into a global algorithm for query optimization that utilizes all features of the considered KBMS. >

Abstract: Query expansion (or) is the process of supplement ing or replacing the original query terms with additional terms either at the search formulation or search reformulation stages This can he done automatically by the system or semi-automatically with asststance from the user. Different approaches to implementing or are considered in three on line catalogues. An evaluative study of an automatic on facil ity in ONNPI. an experimental system developed at City Uni versity, revealed that expanded searches were useful to a substantial proportion of users.

Abstract: This analysis is a panel discussion. There are many problems in the field of image database management. The object-oriented paradigm has been and continues to be a great impetus to this work. The semantics of images is essentially what they contain, and unless there is an effective method to identify their contents and index them on that basis, the database will degenerate to a collection of patterns with no semantics. This is the most challenging issue facing multimedia information systems in general, and image databases in particular. Work on query by image content has barely begun to scratch the surface. A few key query primitives will become well-understood and widely supported. To allow users to browse and search through information domains using sophisticated querying techniques that include imprecise queries, user-directed query processing, and queries that use similarity measures in order to retrieve data, new data modeling approaches are required. Key problems that arise in providing query by image content are considered. >

Abstract: Inexperienced users of online medical databases often do not know how to formulate their queries for effective searches. Previous attempts to help them have provided some standard procedures for query formulation, but depend on the user to enter the concepts of a query properly so that the correct search strategy will be formed. Intelligent assistance specific to a particular query often is not given. Several systems do refine the initial strategy based on relevance feedback, but usually do not make an effort to determine how well-formed a query is before actually performing the search. As part of the Interactive Query Workstation (IQW), we have developed an expert system, Questions and Answers (Q&A), that assists in formulating an initial strategy given concepts entered by the user and that determines if the strategy is well-formed, refining it when necessary.

Abstract: The authors present a data model for office documents and a practically useful algebraic language for the retrieval and manipulation of such objects. A document in the model is represented in a structured form, called a 'frame instance'. Users can group different frame instances into a folder. The algebra offers operations to manipulate both frame instances and folders. They extend the classical relational algebra by associating attributes with types, and supporting attribute inheritance. They also provide aggregate operators which can be applied to different frame instances in a folder. The proposed algebra is used as a sound basis to express the semantics of a high level query language for an office information system. >

Abstract: Statistical Databases usually allow only statistical queries. In order to answer a query some kind of summarization must be performed on the raw data. If the size of the original data is too large, e.g. as in Census data and the Current Population Survey, obtaining accurate answers is extremely time consuming. Thus, if the application allows for some precision loss in the answer, the mechanism for query answering could take advantage of previously computed summaries to answer other summary queries. In this paper we describe the necessary notions to maintain a database of previously computed summary information to allow fast query answering of new summary queries with a qualified accuracy and without having to go back to the original data. We use the concept of summary tables, study the potential of sets of summary tables for answering queries, and organize these sets in a lattice structure.

Abstract: It is known [1] that the class of deterministic finite automata is polynomial time learnable by using membership and equivalence queries. We investigate — the query complexity — the number of membership and equivalence queries for learning deterministic finite automata. We first show two lower bounds in two different learning situations. Then we investigate the query complexity in general setting, and show some trade-off phenomenon between the number of membership and equivalence queries.

Abstract: A novel algorithm to efficiently process a query in a multidatabase environment is devised. The proposed approach reduces data movement between sites and local processing time by allowing local selection and projection for a user query. Also, the algorithm efficiently removes null values incurred due to an outer join by generating the results as a set of sets, gives users more accurate information by presenting all data values for an overlap part, and gives users flexibility by enabling them to define their own processing strategy at a query time. >

Abstract: In this paper we describe a technique for performing shaped-based content retrieval of images from a large database. In order to be able to formulate such user-generated queries about visual objects, we have developed an hierarchical classification technique. This hierarchical classification technique enables similarity matching between objects, with the position in the hierarchy signifying the level of generality to be used in the query. The classification technique is unsupervised, robust, and general; it can be applied to any suitable parameter set. To establish the potential of this classifier for aiding visual querying, we have applied it to the classification of the 2-D outlines of leaves.© (1992) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Abstract: We present a query system for an object-oriented biomedical imaging database containing 3-D anatomical structures and their corresponding 2-D images. The graphical interface facilitates the formation of spatial queries, nonspatial or symbolic queries, and combined spatial/symbolic queries. A query editor is used for the creation and manipulation of 3-D query objects as volumes, surfaces, lines, and points. Symbolic predicates are formulated through a combination of text fields and multiple choice selections. Query results, which may include images, image contents, composite objects, graphics, and alphanumeric data, are displayed in multiple views. Objects returned by the query may be selected directly within the views for further inspection or modification, or for use as query objects in subsequent queries. Our image database query system provides visual feedback and manipulation of spatial query objects, multiple views of volume data, and the ability to combine spatial and symbolic queries. The system allows for incremental enhancement of existing objects and the addition of new objects and spatial relationships. The query system is designed for databases containing symbolic and spatial data. This paper discuses its application to data acquired in biomedical 3- D image reconstruction, but it is applicable to other areas such as CAD/CAM, geographical information systems, and computer vision.© (1992) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Abstract: Deductive databases extend the power of traditional database query languages such as SQL by allowing recursive definitions of predicates. Bottom-up query evaluation is an important query evaluation mechanism for deductive databases and logic programs. In recent years, deductive databases have been extended by allowing facts to contain complex terms that can possibly include variables, and by allowing the use of aggregate operations on sets of answers. This thesis addresses optimization issues related to these extensions. In the first part of the thesis we compare bottom-up and Prolog query evaluation. We show that using existing techniques, bottom-up evaluation performs no more "actions" than (a model of) Prolog for a restricted class of programs, but this does not hold for all programs. We develop rewrite-based optimization techniques that help us extend the above results to all logic programs. We then develop novel techniques for evaluating these rewritten programs. We compare bottom-up query evaluation (using our rewrite optimizations along with our evaluation optimization) with Prolog query evaluation, and show the following. Suppose we are given a program; if (our model of) Prolog evaluation of a query takes time t on a database, bottom-up query evaluation on the database, without subsumption checking, takes time $O(t\cdot$log log t). For a restricted class of programs, bottom-up query evaluation on the database, with subsumption checking, takes time at worst O(t). (In both cases, the time taken by bottom-up evaluation also depends on the size of the program, which we assume to be small.) On the other hand, for many programs, Prolog is arbitrarily slower than bottom-up evaluation. Our optimization techniques are of importance in evaluating programs that generate facts containing variables. In the second part of the thesis, we develop optimizations related to the use of aggregate operations such as min or max. We show how to view several such operations as "selections", and how to propagate these selections into programs. We demonstrate the power and utility of the optimization techniques, using programs for problems such as computing shortest paths and critical paths.

Abstract: This data query apparatus consists of an application software and a circuitry for the processing of the data selection condition of the user query embodied in a host data base management system or information retrieval system. The application software translates the selection condition into the standard form which the circuitry can process. From the host system, and for each data record to be analyzed, the circuit apparatus receives the logical values taken on by the atomic conditions of the query and returns the logical value that the global selection condition takes on. This system allows the user to query the data on the basis of any truth-valued logic set up an arbitrary number of logical values, within the limits fixed by the system developer.

Abstract: This paper discusses the newly developed USMARC Format for Classification Data It reviews its potential uses within an online system and its development as one of the USMARC standards It provides a summary of the fields in the format and considers the prospects for its implementation The paper describes an experiment currently being conducted at the Library of Congress to create USMARC classification records and use a classification database in classifying materials in the social sciences The Library of Congress recently completed the development of a machine-readable format for classification data to allow for the communication of classification records between systems and to provide a standard for the storage of classification data in the computer The USMARC Format for Classification Data joins the family of machine-readable cataloging (MARC) formats: bibliographic, authority, and holdings formats Implementation poses great challenges for institutions, particularly for those responsible for the maintenance of library classification schemes POTENTIAL USES FOR ONLINE CLASSIFICATION Online classification data have many potential uses for information access They may provide the authority for classification numbers, terms, and shelflist information; they may be used for printing and maintaining a classification scheme; and they may enhance subject retrieval, assist the classifier, facilitate maintenance tasks for classification numbers in bibliographic records, and provide the basis for an online shelflist Authority Control for Classification Data Online classification data may provide authority control for the classification number and caption(a heading that corresponds to a classification number(s) and describes the subject covered) An authoritative file of classification records may be used by the classifier to assign classification numbers to bibliographic records It may also provide a system with the mechanism to validate the correct assignment of classification numbers In addition, it can provide authority control for synthesized classification numbers, ie, numbers that have been made more specific by adding other numbers frown a table or other parts of the schedule to a base number A synthesized classification number need not appear in the classification scheme itself, since it is built by following add instructions, which instruct the classifier to add or append other numbers from the schedule or a table to a base number Creating a classification record for a synthesized number can provide an authority for that number and facilitate its further use Printing and Maintenance of Classification Schedules Online classification data could be an efficient method for printing a classification schedule However, a print program for publishing the schedules will have different system requirements than the program for online display Specifications will need to be developed when implementing an online classification system and print program The two major classification schemes in use in the United States, the Library of Congress Classification (LCC) and the Dewey Decimal Classification (DDC), have been developed, produced, and maintained very differently over file years LCC is an enumerative scheme, with new classification numbers inserted where appropriate, and individual changes communicated through the publication LC Classification--Additions and Changes DDC is hierarchical and uses number building extensively by appending numbers from other parts of the schedule onto a base number to create a more specific classification number Revised editions of the whole scheme or of special sections have communicated changes to users; it is currently in its twentieth edition The LCC, now consisting of forty-six separate schedules, was developed over a period of time by different people It was designed as a shelf location and browsing device and has been maintained as such …

Abstract: DB2 is a major relational database system on IBM main frames, it has over six thousand licenses over the world to support a very large number of major applications for customer business, Optimizer in DB2 is a critical component for the query processing, it inherited system R technologies and has been improved in very many aspects from numerous valuable real life experiences on customer applications. The major DB2 optimizer enhancements will be discussed with the backgrounds and examples. A wish list for future enhancements as well as some trend and direction of DB2 optimizer will also be discussed.

Abstract: : This thesis presents the approach of Kaleidoscope, a cooperative query interface for relieving the user's burden of learning and recalling. Kaleidoscope provides the user with an English-like query language (EnQL) for interaction with database systems. It guides the user's query formulation actively via a sequence of menu interactions. Based on a grammar specifying the syntax and semantics of EnQL, the interface proposes legitimate query constituents step by step as menu choices. The objective of this grammar-driven menu guidance is to enable users to construct a meaningful query by recognizing choices that match their mental query. The interface provides additional intraquery conceptual guidance to ensure the integrity of a partial query.