Orkunt Sabuncu

An ontology-based retrieval system using semantic indexing

In this paper, we present an ontology-based information extraction and retrieval system and its application to soccer domain. In general, we deal with three issues in semantic search, namely, usability, scalability and retrieval performance. We propose a keyword-based semantic retrieval approach. The performance of the system is improved considerably using domain-specific information extraction, inference and rules. Scalability is achieved by adapting a semantic indexing approach. We implement the system using the state-of-the-art technologies in Semantic Web and evaluate the performance against traditional systems. Further detailed evaluation is provided to observe the performance gain due to domain-specific information extraction and inference.

An incremental answer set programming based system for finite model computation

We address the problem of Finite Model Computation (FMC) of first-order theories and show that FMC can efficiently and transparently be solved by taking advantage of a recent extension of Answer Set Programming (ASP), called incremental Answer Set Programming (iASP). The idea is to use the incremental parameter in iASP programs to account for the domain size of a model. The FMC problem is then successively addressed for increasing domain sizes until an answer set, representing a finite model of the original first-order theory, is found. We implemented a system based on the iASP solver iClingo and demonstrate its competitiveness by showing that it slightly outperforms the winner of the FNT division of CADEs 2009 Automated Theorem Proving (ATP) competition on the respective benchmark collection.

Ricochet Robots: A Transverse ASP Benchmark

A distinguishing feature of Answer Set Programming is its versatility. In addition to satisfiability testing, it offers various forms of model enumeration, intersection or unioning, as well as optimization. Moreover, there is an increasing interest in incremental and reactive solving due to their applicability to dynamic domains. However, so far no comparative studies have been conducted, contrasting the respective modeling capacities and their computational impact. To assess the variety of different forms of ASP solving, we propose Alex Randolphs board game Ricochet Robots as a transverse benchmark problem that allows us to compare various approaches in a uniform setting. To begin with, we consider alternative ways of encoding ASP planning problems and discuss the underlying modeling techniques. In turn, we conduct an empirical analysis contrasting traditional solving, optimization, incremental, and reactive approaches. In addition, we study the impact of some boosting techniques in the realm of our case study.

Event boundary detection using audio-visual features and web-casting texts with imprecise time information

We propose a method to detect events and event boundaries in soccer videos by using web-casting texts and audio-visual features. The events and their inaccurate time information given in web-casting texts need to be aligned with the visual content of the video. We overcome this issue by utilizing textual, visual and audio features. Existing methods assume that the time at which the event occurs is given precisely (in seconds). However, most web-casting texts presented by popular organizations such as uefa.com (the official site of Union of European Football Associations) provide the time information in minutes rather than seconds. We propose a robust method which is able to handle uncertainties in the time points of the events. As a result of our experiments, we claim that our method detects event boundaries satisfactorily for uncertain web-casting texts, and that the use of audio-visual features improves the performance of event boundary detection.

Integrating ASP into ROS for Reasoning in Robots

Knowledge representation and reasoning capacities are vital to cognitive robotics because they provide higher level functionalities for reasoning about actions, environments, goals, perception, etc. Although Answer Set Programming (ASP) is well suited for modelling such functions, there was so far no seamless way to use ASP in a robotic setting. We address this shortcoming and show how a recently developed ASP system can be harnessed to provide appropriate reasoning capacities within a robotic system. To be more precise, we furnish a package integrating the new version of the ASP solver clingo with the popular open-source robotic middleware Robot Operating System (ROS). The resulting system, ROSoClingo, provides a generic way by which an ASP program can be used to control the behaviour of a robot and to respond to the results of the robot’s actions.

Fostering social interaction of home-bound elderly people: the easyreach system

This paper presents the EasyReach system, a tool that aims at getting the elderly and pre-digital divide population closer to new technologies by creating a simplified social enviroment that facilitates interaction, trying to allow them to (i) easily keep in contact with friends and relatives, (ii) share their lifetime expertise, and (iii) avoid isolation. The EasyReach tool creates for the elderly a special social TV channel accessed by means of their own TV set and a specialized remote control endowed with gesture recognition, video and audio capture capabilities. A hidden personal assistant reasons on user preferences in the background allowing better focalization on his/her social interests.

Matchmaking with Answer Set Programming

Matchmaking is a form of scheduling that aims at bringing companies or people together that share common interests, services, or products in order to facilitate future business partnerships.We begin by furnishing a formal characterization of the corresponding multi-criteria optimization problem.We then address this problem by Answer Set Programming in order to solve real-world matchmaking instances, which were previously dealt with by special-purpose algorithms.

Finite model computation via answer set programming

We show how Finite Model Computation (FMC) of first-order theories can efficiently and transparently be solved by taking advantage of an extension of Answer Set Programming, called incremental Answer Set Programming (iASP). The idea is to use the incremental parameter in iASP programs to account for the domain size of a model. The FMC problem is then successively addressed for increasing domain sizes until an answer set, representing a finite model of the original first-order theory, is found. We developed a system based on the iASP solver iClingo and demonstrate its competitiveness.

Ontological video annotation and querying system for soccer games

This paper describes a video annotation and querying system which is capable of semi-automatic annotation of videos from text. The extracted metadata is aligned with the corresponding video segments. This allows users to query videos according to their semantic content. We have chosen soccer domain to demonstrate the use of the system. The soccer videos are very suitable for our framework, since it is easy to find Web-cast match reports for soccer games. The annotated videos are stored in MPEG-7 format in an object-oriented database. The keyword-based indexing allows fast retrieval of video segments. The system accepts match reports in Turkish which makes querying in Turkish possible.

Using Criticalities as a Heuristic for Answer Set Programming

Answer Set Programming is a new paradigm based on logic programming. The main component of answer set programming is a system that finds the answer sets of logic programs. During the computation of an answer set, systems are faced with choice points where they have to select a literal and assign it a truth value. Generally, systems utilize some heuristics to choose new literals at the choice points. The heuristic used is one of the key factors for the performance of the system.