<p>The use for a readability classification model is mainly as an integrated part of an information retrieval system. By matching the user's demands of readability to the documents with the corresponding readability, the classification model can further improve the results of, for example, a search engine. This thesis presents a new solution for classification into readability levels for Swedish. The results from the thesis are a number of classification models. The models were induced by training a Support Vector Machines classifier on features that are established by previous research as good measurements of readability. The features were extracted from a corpus annotated with three readability levels. Natural Language Processing tools for tagging and parsing were used to analyze the corpus and enable the extraction of the features from the corpus. Empirical testings of different feature combinations were performed to optimize the classification model. The classification models render a good and stable classification. The best model obtained a precision score of 90.21\% and a recall score of 89.56\% on the test-set, which is equal to a F-score of 89.88.</p> / <p>Uppsatsen beskriver utvecklandet av en klassificeringsmodell för Svenska texter beroende på dess läsbarhet. Användningsområdet för en läsbaretsklassificeringsmodell är främst inom informationssökningssystem. Modellen kan öka träffsäkerheten på de dokument som anses relevanta av en sökmotor genom att matcha användarens krav på läsbarhet med de indexerade dokumentens läsbarhet. Resultatet av uppsatsen är ett antal modeller för klassificering av text beroende på läsbarhet. Modellerna har tagits fram genom att träna upp en Support Vector Machines klassificerare, på ett antal särdrag som av tidigare forskning har fastslagits vara goda mått på läsbarhet. Särdragen extraherades från en korpus som är annoterad med tre läsbarhetsnivåer. Språkteknologiska verktyg för taggning och parsning användes för att möjliggöra extraktionen av särdragen. Särdragen utvärderades empiriskt i olika särdragskombinationer för att optimera modellerna. Modellerna testades och utvärderades med goda resultat. Den bästa modellen hade en precision på 90,21 och en recall på 89,56, detta ger en F-score som är 89,88. Uppsatsen presenterar förslag på vidareutveckling samt potentiella användningsområden.</p>

Although there is research into student learning on the Web and other computer-supported environments, there has been little investigation into the practice and pedagogy of university Web teachers. This qualitative study used a series of interviews of eight higher education faculty to gather data on their Web teaching practices, and an examination of their Web courses to identify their pedagogies. There was a notable difference in the way the four teachers with Web-assisted courses and the four teachers with Web-only courses used the Web in their teaching. Those with Web-assisted courses used the Web primarily as a connection to expanded resources and a supplement to their face-to-face teaching. Those who taught Web-only courses used the Web for resource access, and also used asynchronous dialogue and peer interactions to support student construction of knowledge. Moreover, the Web-only teachers reported a shift in their roles from lecturer and expert in the classroom to facilitator and co-learner as Web teachers. Four aspects of the Web teaching environment appear to be foundational in supporting an effective Web pedagogy: (1) the varied and extensive uses of e-mail, (2) the "think time" made possible by asynchronous dialogue, (3) distributed, hyperlinked learning, and (4) a reported shift from a content focus to process and issues because Web instructors are confident that the material is presented in the Web course as they wish it. The experiences of the Web teachers in the study would indicate that these four elements can be leveraged to improve university Web teaching and deepen student learning, perhaps even beyond results capable of achievement in face-to-face teaching. / Graduation date: 1999

As the World Wide Web continues to grow, people clearly want to do much more with it than just publish static pages of text and graphics. While such increased interactivity has traditionally been accomplished through the use of server-side CGI scripts, much recent research on Web browsers has been on extending their capabilities through the addition of various types of client-side services. The most popular of these extensions take the form of plug-ins, applets, and "document scripts" such as Java Script. However, because these extensions have been created in a haphazard way by a variety of independent groups, they suffer greatly in terms of flexibility, uniformity, and interoperability. Interactive HTML is a system that addresses these problems by combining plug-ins, applets, and document scripts into one uniform and cohesive architecture. It is implemented as an external C library that can be used by a browser programmer to add client-side services to the browser. The IHTML services are implemented as dynamically loaded "language modules," allowing new plug-ins and language interpreters to be added to an iHTML browser without recompiling the browser itself. The system is currently integrated with NCSA's X Mosaic browser and includes language modules for a text viewer plug-in and Python language interpreter. This thesis examines the iHTML architecture in the context of the historical development of Web client-side services and presents an example of iHTML's use to collect usage information about Web documents. / Graduation date: 1997

Although much effort has been invested to build applications that support group work, collaborative applications have not found easy success. The cost of adopting and maintaining collaborative applications has prevented their widespread use, especially among small distributed groups. Application developers have had difficulties recognizing the extra effort required by groups to use collaborative applications and how to either reduce this effort or provide other benefits to compensate for the extra work. These problems have limited the success of collaborative applications, which have not attained the same level of productivity improvements that single user applications have achieved. In this thesis we present a framework that describes the types of computer support that can facilitate the work of distributed engineering design groups. Our framework addresses support for web-based groups in particular because we believe the web can be a powerful medium for collaboration if accommodated properly. We show how the concepts in this framework can be implemented by prototyping a web-based engineering decision support system. Our framework is a synthesis of ideas motivated by an examination of literature in various fields that share a common interest in collaborative work. It can influence application development by helping developers become aware of the types of support should be considered to aid web-based collaborative design. / Graduation date: 1997

I have invented "Internet Fish," a novel class of resource-discovery tools designed to help users extract useful information from the Internet. Internet Fish (IFish) are semi-autonomous, persistent information brokers; users deploy individual IFish to gather and refine information related to a particular topic. An IFish will initiate research, continue to discover new sources of information, and keep tabs on new developments in that topic. As part of the information-gathering process the user interacts with his IFish to find out what it has learned, answer questions it has posed, and make suggestions for guidance. Internet Fish differ from other Internet resource discovery systems in that they are persistent, personal and dynamic. As part of the information-gathering process IFish conduct extended, long-term conversations with users as they explore. They incorporate deep structural knowledge of the organization and services of the net, and are also capable of on-the-fly reconfiguration, modification and expansion. Human users may dynamically change the IFish in response to changes in the environment, or IFish may initiate such changes itself. IFish maintain internal state, including models of its own structure, behavior, information environment and its user; these models permit an IFish to perform meta-level reasoning about its own structure. To facilitate rapid assembly of particular IFish I have created the Internet Fish Construction Kit. This system provides enabling technology for the entire class of Internet Fish tools; it facilitates both creation of new IFish as well as additions of new capabilities to existing ones. The Construction Kit includes a collection of encapsulated heuristic knowledge modules that may be combined in mix-and-match fashion to create a particular IFish; interfaces to new services written with the Construction Kit may be immediately added to "live" IFish. Using the Construction Kit I have created a demonstration IFish specialized for finding World-Wide Web documents related to a given group of documents. This "Finder" IFish includes heuristics that describe how to interact with the Web in general, explain how to take advantage of various public indexes and classification schemes, and provide a method for discovering similarity relationships among documents.

Despite the vast amount of research that has been devoted separately to the topics of browsing and Really Simple Syndication (RSS) aggregation architecture, little is known about how end-users engage with RSS feeds and how they browse while using a feed aggregate. This study explores the browsing behaviors end-users exhibit when using RSS and Atom feeds. The researcher analyzed end-users’ browsing experiences and discusses browsing variations. The researcher observed, tested, and interviewed eighteen (N=18) undergraduate students at the University of Tennessee to determine how end-users engage with RSS feeds. This study evaluates browsing using two variations of tasks, (1) an implicit task with no final goal and (2) an explicit task with a final goal. The researcher observed the participants complete the two tasks and conducted exit interviews, which addressed the end-users’ experiences with Google Reader and provided further explanation of browsing behaviors. The researcher analyzed the browsing behaviors based upon Bates’ (2007) definitions and characteristics of browsing. The results of this exploratory research provide insights into end-user interaction with RSS feeds.

This paper seeks to describe the process by which a database-centric web application was redesigned and rewritten to take advantage of Apache’s Lucene - an open-source information retrieval software library written in the Java programming language. After the implementation of a Lucene-based text index of “semi-structured data”, a college radio station's card catalog application was able to deliver higher-quality search results in significantly less time than it was able to do using just a relational database alone. Additionally, the dramatic improvements in speed and performance even allowed the search results interface to be redesigned and enhanced with an improved pagination system and new features such as faceted search/filtering.

Les ontologies modélisent la connaissance d'un domaine avec une hiérarchie de concepts. Cette thèse porte sur leur utilisation dans les Systèmes de Recherche d'Information (SRI) pour estimer la pertinence des documents par rapport à une requête. Nous calculons cette pertinence à l'aide d'un modèle des préférences de l'utilisateur et d'une mesure de similarité sémantique associée à l'ontologie. Cette approche permet d'expliquer à l'utilisateur pourquoi les documents sélectionnés sont pertinents grâce à une visualisation originale. La RI étant un processus itératif, l'utilisateur doit être guidé dans sa reformulation de requête. Une stratégie de reformulation de requêtes conceptuelles est formalisée en un problème d'optimisation utilisant les retours faits par l'utilisateur sur les premiers résultats proposés comme base d'apprentissage. Nos modèles sont validés sur la base de performances obtenues sur des jeux de tests standards et de cas d'études impliquant des experts biologistes.

Microblogging is an increasingly popular form of social media. One of the most popular microblogging services is Twitter. The number of messages posted to Twitter on a daily basis is extremely large. Accordingly, it becomes hard for users to sort through these messages and find ones that interest them. Twitter offers search mechanisms but they are relatively simple and accordingly the results can be lacklustre. Through participation in the 2011 Text Retrieval Conference's Microblog Track, this thesis examines real-time ad hoc search using standard information retrieval approaches without microblog or Twitter specific modifications. It was found that using pseudo-relevance feedback based upon a language model derived from Twitter posts, called tweets, in conjunction with standard ranking methods is able to perform competitively with advanced retrieval systems as well as microblog and Twitter specific retrieval systems. Furthermore, possible modifications both Twitter specific and otherwise are discussed that would potentially increase retrieval performance. Twitter has also spawned an interesting phenomenon called hashtags. Hashtags are used by Twitter users to denote that their message belongs to a particular topic or conversation. Unfortunately, tweets have a 140 characters limit and accordingly all relevant hashtags cannot always be present in tweet. Thus, Twitter users cannot easily find tweets that do not contain hashtags they are interested in but should contain them. This problem is investigated in this thesis in three ways using learning methods. First, learning methods are used to determine if it is possible to discriminate between two topically different sets of a tweets. This thesis then investigates whether or not it is possible for tweets without a particular hashtag, but discusses the same topic as the hashtag, to be separated from random tweets. This case mimics the real world scenario of users having to sift through random tweets to find tweets that are related to a topic they are interested in. This investigation is performed by removing hashtags from tweets and attempting to distinguish those tweets from random tweets. Finally, this thesis investigates whether or not topically similar tweets can also be distinguished based upon a sub-topic. This was investigated in almost an identical manner to the second case. This thesis finds that topically distinct tweets can be distinguished but more importantly that standard learning methods are able to determine that a tweet with a hashtag removed should have that hashtag. In addition, this hashtag reconstruction can be performed well with very few examples of what a tweet with and without the particular hashtag should look like. This provides evidence that it may be possible to separate tweets a user may be interested from random tweets only using hashtags they are interested in. Furthermore, the success of the hashtag reconstruction also provides evidence that users do not misuse or abuse hashtags since hashtag presence was taken to be the ground truth in all experiments. Finally, the applicability of the hashtag reconstruction results to the TREC Microblog Track and a mobile application is presented.

Informationssökningar av olika slag sker dagligen världen över och sökresultatet kan många gånger vara så stort att användarna har svårt att veta vilka sökresultat som är relevanta. I denna uppsats har syftet varit att undersöka hur sökresultat kan filtreras och sorteras med hjälp av platsbaserad sökning för att det ska bli mer relevant för användaren. Genom litteraturstudie och intervjuer har det blivit möjligt att ta reda på hur ett sökresultat skulle kunna filtreras och sorteras för att möta användarnas förväntningar. De teorier och slutsatser som framkom tillämpades vid utvecklingen av en prototyp. Prototypen testades och utvärderades sedan genom ett användartest där resultatet visar att filtreringen och sorteringen som används i studien kan göra sökresultatet mer relevant för användaren. / Information searches of various kinds take place daily around the world and search results can often be so large that users have difficulty knowing which results are relevant. In this paper the aim has been to examine how search results can be filtered and sorted by using location-based search to make the results more relevant to the user. Through a literature review and interviews it was possible to investigate how a search result can be filtered and sorted to meet user expectations. The theories and conclusions that emerged were applied in the development of a prototype. Usability tests were performed on the prototype and the results show that the filtering used in the study can provide a more relevant search result.