Slobodanka Djordjevic-Kajan

Searching for similar trajectories in spatial networks

In several applications, data objects move on pre-defined spatial networks such as road segments, railways, and invisible air routes. Many of these objects exhibit similarity with respect to their traversed paths, and therefore two objects can be correlated based on their motion similarity. Useful information can be retrieved from these correlations and this knowledge can be used to define similarity classes. In this paper, we study similarity search for moving object trajectories in spatial networks. The problem poses some important challenges, since it is quite different from the case where objects are allowed to move freely in any direction without motion restrictions. New similarity measures should be employed to express similarity between two trajectories that do not necessarily share any common sub-path. We define new similarity measures based on spatial and temporal characteristics of trajectories, such that the notion of similarity in space and time is well expressed, and moreover they satisfy the metric properties. In addition, we demonstrate that similarity range queries in trajectories are efficiently supported by utilizing metric-based access methods, such as M-trees.

An architecture for interoperable GIS use in a local community environment

Many organizations in the local community environment use and produce geospatial data. An increasing number of geodata producers and users have expressed the need for the integration of geodata and for interoperable geographic information systems (GIS). Each of these user groups has a different view of the world and available information is always distributed and mostly heterogeneous. Wrappers and mediation may resolve structural and syntactic heterogeneity. However, domain experts use the concepts and terminology specific to their fields of expertise, and use different parameters to express their model of a concept. Such semantic heterogeneity of data sources causes serious problems, which may be resolved by ontologies. The goal of our research is to define an architecture, called GeoNis, for semantic interoperability of distributed and heterogeneous GIS in a local community environment. The proposed architecture is based on mediation and ontologies. GeoNis solution to the problem of semantic heterogeneity is to formally specify the meaning of the terminology of each community using local ontology and to define a translation between each community terminologies and an intermediate terminology represented by top-level ontology and common data model.

Trajectory Similarity Search in Spatial Networks

In several applications, data objects are assumed to move on predefined spatial networks such as road segments, railways, and invisible air routes. Moving objects may exhibit similarity with respect to their traversed paths, and therefore two objects can be correlated based on their path similarity. In this paper, we study similarity search for moving object trajectories for spatial networks. The problem poses some important challenges, since it is quite different from the case where objects are allowed to move without motion restrictions. Experimental results performed on real-life spatial networks show that trajectory similarity can be supported in an effective and efficient manner by using metric-based access methods

Continuous range monitoring of mobile objects in road networks

In contrast to regular queries that are evaluated only once, a continuous query remains active over a period of time and has to be continuously evaluated to provide up to date answers. We propose a method for continuous range query processing for different types of queries, characterized by mobility of objects and/or queries which all follow paths in an underlying spatial network. The method assumes an available 2D indexing scheme for indexing spatial network data. An appropriately extended R*-tree, that primarily is used as an indexing scheme for network segments, provides matching of queries and objects according to their locations on the network or their network routes. The method introduces an additional pre-refinement step which generates main-memory data structures to support efficient, incremental reevaluation of continuous range queries in periodically performed refinement steps.

INSTRUCT: Modeling students by asking questions

The paper reports an approach to inducing models of procedural skills from observed student performance. The approach, referred to as INSTRUCT, builds on two well-known techniques, reconstructive modeling and model tracing, at the same time avoiding their major pitfalls. INSTRUCT does not require prior empirical knowledge of student errors and is also neutral with respect to pedagogy and reasoning strategies applied by the student. Pedagogical actions and the student model are generated on-line, which allows for dynamic adaptation of instruction, problem generation and immediate feedback on students errors. Furthermore, the approach is not only incremental but truly active, since it involves students in explicit dialogues about problem-solving decisions. Student behaviour is used as a source of information for user modeling and to compensate for the unreliability of the student model. INSTRUCT uses both implicit information about the steps the student performed or the explanations he or she asked for, and explicit information gained from the students answers to direct question about operations being performed. Domain knowledge and the user model are used to focus the search on the portion of the problem space the student is likely to traverse while solving the problem at hand. The approach presented is examined in the context of SINT, an ITS for the domain of symbolic integration.

Bridging objects and relations: a mediator for an OO front-end to RDBMSs

Abstract An object-oriented paradigm is established as the leading approach for developing non-traditional applications, such as GIS or multimedia systems. On the other hand, relational databases have dominated the area of data processing in the past decade. These two trends motivate the research on integrating OO applications with relational databases. This paper presents our approach to the symbiosis of the OO and relational data models, which is built into GinisNT , a scalable OO GIS framework based on an OO-to-relational mapping algorithm. The mapping algorithm transforms classes and objects into relations and tuples, and vice versa, instantiates objects from relational databases. The methodology presented here is extremely efficient, as has been proved by a number of applications developed in GinisNT , and is at the same time cost efficient, as it builds upon existing platforms.

Prediction of bus motion and continuous query processing for traveler information services

The paper presents the methods for prediction of bus arrival times and continuous query processing as foundations of traveler information services. The time series of data from automatic vehicle location (AVL) system, consisting of time, location and speed data, is used with historical statistics and bus schedule information to predict future arrivals and motion. Based on predicted and AVL data, continuous query processing technique is proposed to extend traveler information service with notification/alarm features. Extensive experiments have shown that the proposed algorithm for bus motion prediction is efficient enough to function in real conditions and that augmented with continuous query processing techniques can produce services that useful to the travelers.

Visual query and analysis tool of the object-relational GIS framework

Information Systems (GISs) have become an essential tool for efficient handling of our natural and artificial environment. The most important activities in a GIS are querying and spatial analysis of georeferenced data providing decision making and problem solving support. Traditional database query languages and tools are inappropriate for GIS purpose, because of their inability to address spatial properties of the real world entities. This paper presents a spatial query and analysis tool with the strong visual context, called GeoQA. It has been developed as an integral component of the GinisNT, object-oriented GIS framework for GIS applications development. GeoQA provides effective, interactive but user-friendly and ease-of-use mechanisms for performing spatial and non-spatial queries, as well as, spatial, thematic and statistic analysis in specific GIS applications developed on the top of GinisNT.

Interactive reconstructive student modeling: A machine‐learning approach

Reconstructive bug modeling is a well‐known approach to student modeling in intelligent tutoring systems, suitable for modeling procedural tasks. Domain knowledge is decomposed into the set of primitive operators and the set of conditions of their applicability. Reconstructive modeling is capable of describing errors that come from irregular application of correct operators. The main obstacle to successfulness of this approach is such decomposition of domain knowledge to primitive operators with a very low level of abstraction so that bugs could never occur within them. The other drawback of this modeling scheme is its efficiency because it is usually done offline, due to vast search spaces involved. This article reports a novel approach to reconstructive modeling based on machine‐learning techniques for inducing procedures from traces. The approach overcomes the problems of reconstructive modeling by its interactive nature. It allows online model generation by using domain knowledge and knowledge about t...

Incremental evaluation of continuous range queries over objects moving on known network paths

In this paper we address the problem and propose the method for continuous range query processing for mobile objects moving on known network paths. The method assumes that the objects know their destination in advance and move along the best/shortest path to it. The method is based on an available 2D indexing scheme (e.g. R* Tree) for indexing transportation network data. The network R* tree is extended to provide matching of queries and objects according to their locations on the network for stationary objects/queries or their network routes for mobile objects/queries and performing the filter step of the continuous query. The refinement step of the query processing methodology generates main memory data structures that represent temporal query result and support periodic, incremental evaluation to produce result updates.