Browsing by Subject "Information services"
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Item Open Access Analyzing Turkish e-government websites by eye tracking(IEEE, 2013) Albayrak, Duygu; Çaģiltay, K.Usability studies provide essential information about users' views and perceptions of efficiency, effectiveness and satisfaction of given online services. Nowadays, e-government web sites become popular. Therefore, there is a need for usability testing to specify the usability problems and to make the services of the e-government more usable. The purpose of this study is to investigate usability of some Turkish e-government services. The study examined usability of five Turkish e-government web sites: Ministry of National Education - Student Information System (eokul), Ministry of Justice - National Judicial Network Project (UYAP), Turkish National Police: Vehicle Search System, Social Security Institute: Service Details and General Directorate of Land Registry and Cadastre. It was conducted with nine participants. This study is a case study with mixed design methodology, in which both quantitative and qualitative approaches were employed and combined. Quantitative data were collected through an eye-tracker, a pre-test questionnaire of participants' demographics and previous utilization of egovernment web sites and a post-test questionnaire. Qualitative data were collected through both semi-structured individual interviews and observation during test. The study results identify the usability problems encountered while using government services. The study concludes with specific recommendations for improvement of e-government services in Turkey. © 2013 IEEE.Item Open Access Authorship attribution: performance of various features and classification methods(IEEE, 2007-11) Bozkurt, İlker Nadi; Bağlıoğlu, Özgür; Uyar, ErkanAuthorship attribution is the process of determining the writer of a document. In literature, there are lots of classification techniques conducted in this process. In this paper we explore information retrieval methods such as tf-idf structure with support vector machines, parametric and nonparametric methods with supervised and unsupervised (clustering) classification techniques in authorship attribution. We performed various experiments with articles gathered from Turkish newspaper Milliyet. We performed experiments on different features extracted from these texts with different classifiers, and combined these results to improve our success rates. We identified which classifiers give satisfactory results on which feature sets. According to experiments, the success rates dramatically changes with different combinations, however the best among them are support vector classifier with bag of words, and Gaussian with function words. ©2007 IEEE.Item Open Access Coaching engineering freshmen at Bilkent University(Middle East Technical University, Faculty of Engineering, 2005) Özdemir, B. U.; Verhoeven, J. M.; Çelik, B. K.In September 2003, the Faculty of Engineering at Bilkent University created an office to help first year students adapt to university life and start their academic studies effectively. For each of the three Departments of the Faculty, an 'academic student coordinator' offers personal coaching and consulting services for each individual student; the coordinator follows the progress of the students and contacts and advises them if necessary. The office offers an Engineering Orientation course that covers time management, study skills, problem solving and critical thinking. Besides this, the office offers tutorial sessions for physics courses, and organizes social activities.Item Open Access Cover coefficient-based multi-document summarization(Springer, 2009-04) Ercan, Gönenç; Can, FazlıIn this paper we present a generic, language independent multi-document summarization system forming extracts using the cover coefficient concept. Cover Coefficient-based Summarizer (CCS) uses similarity between sentences to determine representative sentences. Experiments indicate that CCS is an efficient algorithm that is able to generate quality summaries online. © Springer-Verlag Berlin Heidelberg 2009.Item Open Access A graph based approach to estimating lexical cohesion(ACM, 2008) Gürkök, Hayrettin; Karamuftuoglu, Murat; Schaal, MarkusTraditionally, information retrieval systems rank documents according to the query terms they contain. However, even if a document may contain all query terms, this does not guarantee that it is relevant to the query. The query terms can occur together in the same document, but may have been used in different contexts, expressing separate topics. Lexical cohesion is a characteristic of natural language texts, which can be used to determine whether the query terms are used in the same context in the document. In this paper we make use of a graph-based approach to capture term contexts and estimate the level of lexical cohesion in a document. To evaluate the performance of our system, we compare it against two benchmark systems using three TREC document collections. Copyright 2008 ACM.Item Open Access New event detection and topic tracking in Turkish(John Wiley & Sons, Inc., 2010) Can, F.; Kocberber, S.; Baglioglu, O.; Kardas, S.; Ocalan, H. C.; Uyar, E.Topic detection and tracking (TDT) applications aim to organize the temporally ordered stories of a news stream according to the events. Two major problems in TDT are new event detection (NED) and topic tracking (TT). These problems focus on finding the first stories of new events and identifying all subsequent stories on a certain topic defined by a small number of sample stories. In this work, we introduce the first large-scale TDT test collection for Turkish, and investigate the NED and TT problems in this language. We present our test-collection-construction approach, which is inspired by the TDT research initiative. We show that in TDT for Turkish with some similarity measures, a simple word truncation stemming method can compete with a lemmatizer-based stemming approach. Our findings show that contrary to our earlier observations on Turkish information retrieval, in NED word stopping has an impact on effectiveness. We demonstrate that the confidence scores of two different similarity measures can be combined in a straightforward manner for higher effectiveness. The influence of several similarity measures on effectiveness also is investigated. We show that it is possible to deploy TT applications in Turkish that can be used in operational settings. © 2010 ASIS&T.Item Open Access Novelty detection for topic tracking(John Wiley & Sons, Inc., 2012) Aksoy, C.; Can, F.; Kocberber, S.Multisource web news portals provide various advantages such as richness in news content and an opportunity to follow developments from different perspectives. However, in such environments, news variety and quantity can have an overwhelming effect. New-event detection and topic-tracking studies address this problem. They examine news streams and organize stories according to their events; however, several tracking stories of an event/topic may contain no new information (i.e., no novelty). We study the novelty detection (ND) problem on the tracking news of a particular topic. For this purpose, we build a Turkish ND test collection called BilNov-2005 and propose the usage of three ND methods: a cosine-similarity (CS)-based method, a language-model (LM)-based method, and a cover-coefficient (CC)-based method. For the LM-based ND method, we show that a simpler smoothing approach, Dirichlet smoothing, can have similar performance to a more complex smoothing approach, Shrinkage smoothing. We introduce a baseline that shows the performance of a system with random novelty decisions. In addition, a category-based threshold learning method is used for the first time in ND literature. The experimental results show that the LM-based ND method significantly outperforms the CS- and CC-based methods, and categorybased threshold learning achieves promising results when compared to general threshold learning. © 2011 ASIS&T.Item Open Access A practitioner's guide for static index pruning(Springer, 2009-04) Altıngövde, İsmail Şengör; Özcan, Rıfat; Ulusoy, ÖzgürWe compare the term- and document-centric static index pruning approaches as described in the literature and investigate their sensitivity to the scoring functions employed during the pruning and actual retrieval stages. © Springer-Verlag Berlin Heidelberg 2009.Item Open Access Site-based dynamic pruning for query processing in search engines(ACM, 2008-07) Altıngövde İsmail Şengör; Demir, Engin; Can, Fazlı; Ulusoy, ÖzgürWeb search engines typically index and retrieve at the page level. In this study, we investigate a dynamic pruning strategy that allows the query processor to first determine the most promising websites and then proceed with the similarity computations for those pages only within these sites.Item Open Access Stylistic document retrieval for Turkish(IEEE, 2009-09) Zamalieva, Daniya; Kalaycılar, Fırat; Kale, Aslı; Pehlivan, Selen; Can, FazlıIn information retrieval (IR) systems, there are a query and a collection of documents compared with this query and ranked according to a particular similarity measure. Since texts with the same content can be written by different authors, the writing styles of the documents change as well accordingly. This observation brings the idea of investigating text by means of style. In this paper, we analyze text documents in terms of stylistic features of the written text and measure effectiveness of these features in an IR system. Our main focus is on Turkish text documents. Although there are many studies about broadening IR systems with style based enhancement, there is no similar application for Turkish which performs retrieval depending purely on style. © 2009 IEEE.Item Open Access Turkish keyphrase extraction using multi-criterion ranking(IEEE, 2009-09) Özdemir, Bahadır; Çiçekli, İlyasKeyphrases have been extensively used for indexing and searching in databases and information retrieval systems. In addition, they provide useful information about semantic content of a document. In this paper, we propose an algorithm for automating Turkish keyphrase extraction. Several features of candidate phrases are exploited and form the extraction task as a problem of finding optimal set of candidate phrases. We use multi-criterion ranking to tackle this problem. © 2009 IEEE.