Stanisavljevic Darko, Hasani-Mavriqi Ilire, Lex Elisabeth, Strohmaier M., Helic Denis
2016
In this paper we assess the semantic stability of Wikipedia by investigat-ing the dynamics of Wikipedia articles’ revisions over time. In a semantically stablesystem, articles are infrequently edited, whereas in unstable systems, article contentchanges more frequently. In other words, in a stable system, the Wikipedia com-munity has reached consensus on the majority of articles. In our work, we measuresemantic stability using the Rank Biased Overlap method. To that end, we prepro-cess Wikipedia dumps to obtain a sequence of plain-text article revisions, whereaseach revision is represented as a TF-IDF vector. To measure the similarity betweenconsequent article revisions, we calculate Rank Biased Overlap on subsequent termvectors. We evaluate our approach on 10 Wikipedia language editions includingthe five largest language editions as well as five randomly selected small languageeditions. Our experimental results reveal that even in policy driven collaborationnetworks such as Wikipedia, semantic stability can be achieved. However, there aredifferences on the velocity of the semantic stability process between small and largeWikipedia editions. Small editions exhibit faster and higher semantic stability than large ones. In particular, in large Wikipedia editions, a higher number of successiverevisions is needed in order to reach a certain semantic stability level, whereas, insmall Wikipedia editions, the number of needed successive revisions is much lowerfor the same level of semantic stability.
Kröll Mark, Strohmaier M.
2015
People willingly provide more and more information about themselves on social media platforms. This personal information about users’ emotions (sentiment) or goals (intent) is particularly valuable, for instance, for monitoring tools. So far, sentiment and intent analysis were conducted separately. Yet, both aspects can complement each other thereby informing processes such as explanation and reasoning. In this paper, we investigate the relation between intent and sentiment in weblogs. We therefore extract ~90,000 human goal instances from the ICWSM 2009 Spinn3r dataset and assign respective sentiments. Our results indicate that associating intent with sentiment represents a valuable addition to research areas such as text analytics and text understanding.
Kröll Mark, Strohmaier M.
2010
In this paper, we introduce the idea of Intent Analysis, which is to create a profile of the goals and intentions present in textual content. Intent Analysis, similar to Sentiment Analysis, represents a type of document classification that differs from traditional topic categorization by focusing on classification by intent. We investigate the extent to which the automatic analysis of human intentions in text is feasible and report our preliminary results, and discuss potential applications. Inaddition, we present results from a study that focused on evaluating intent profiles generated from transcripts of American presidential candidate speeches in 2008.
Körner C., Kröll Mark, Strohmaier M.
2009
Understanding search intent is often assumed to represent a critical barrier to the level of service that search engine providers can achieve. Previous research has shown that search queries differ with regard to intentional explicitness. We build on this observation and introduce Intentional Query Suggestion as a novel idea that aims to make searcher’s intent more explicit during search. In this paper, we present an algorithm for Intentional Query Suggestion and corresponding data from comparative experiments with traditional query suggestion mechanisms. Our results suggest that Intentional Query Suggestion 1) diversifies search result sets (i.e. it reduces result set overlap) and 2) exhibits interesting differences in terms of click-through rates
Kröll Mark, Strohmaier M.
2009
Knowledge about human goals has been found to be an important kind of knowledge for a range of challenging problems, such as goal recognition from peoples’ actions or reasoning about human goals. Necessary steps towards conducting such complex tasks involve (i) ac-quiring a broad range of human goals and (ii) making them accessible by structuring and storing them in a knowledge base. In this work, we focus on extracting goal knowledge from weblogs, a largely untapped resource that can be expected to contain a broad variety of hu-man goals. We annotate a small sample of web-logs and devise a set of simple lexico-syntactic patterns that indicate the presence of human goals. We then evaluate the quality of our pat-terns by conducting a human subject study. Re-sulting precision values favor patterns that are not merely based on part-of-speech tags. In fu-ture steps, we intend to improve these prelimi-nary patterns based on our observations
Jeanquartier Fleur, Kröll Mark, Strohmaier M.
2009
Getting a quick impression of the author's intention of a text is a task often performed. An author's intention plays a major role in successfully understanding a text. For supporting readers in this task, we present an intentional approach to visual text analysis, making use of tag clouds. The objectiveof tag clouds is presenting meta-information in a visually appealing way. However there is also much uncertainty associated with tag clouds, such as giving the wrong impression. It is not clear whether the author's intent can be grasped clearly while looking at a corresponding tag cloud. Therefore it is interesting to ask to what extent, with tag clouds, it is possible to support the user in understanding intentions expressed. In order to answer this question, we construct an intentional perspective on textual content. Based on an existing algorithm for extracting intent annotations from textual content we present a prototypical implementation to produce intent tag clouds, and describe a formative testing, illustrating how intent visualizations may support readers in understanding a text successfully. With the initial prototype, we conducted user studies of our intentional tag cloud visualization and a comparison with a traditional one that visualizes frequent terms. The evaluation's results indicate, that intent tag clouds have a positive effect on supporting users in grasping an author's intent.
Strohmaier M., Prettenhofer P., Kröll Mark
2008
On the web, search engines represent a primary instrument through which users exercise their intent. Understanding the specific goals users express in search queries could improve our theoretical knowledge about strategies for search goal formulation and search behavior, and could equip search engine providers with better descriptions of users’ information needs. However, the degree to which goals are explicitly expressed in search queries can be suspected to exhibit considerable variety, which poses a series of challenges for researchers and search engine providers. This paper introduces a novel perspective on analyzing user goals in search query logs by proposing to study different degrees of intentional explicitness. To explore the implications of this perspective, we studied two different degrees of explicitness of user goals in the AOL search query log containing more than 20 million queries. Our results suggest that different degrees of intentional explicitness represent an orthogonal dimension to existing search query categories and that understanding these different degrees is essential for effective search. The overall contribution of this paper is the elaboration of a set of theoretical arguments and empirical evidence that makes a strong case for further studies of different degrees of intentional explicitness in search query logs.
Strohmaier M., Horkoff Jennifer, Yu E., Aranda Jorge, Easterbrook Steve
2008
A considerable amount of effort has been placed into the investigation of i* modeling as a tool for early stage requirements engineering. However, widespread adoption of i* models in the requirements process has been hindered by issues such as the effort required to create the models, coverage of the problem context, and model complexity. In this work, we explore the feasibility of pattern application to address these issues. To this end, we perform both an exploratory case study and initial experiment to investigate whether the application of patterns improves aspects of i* modeling. Furthermore, we develop a methodology which guides the adoption of patterns for i* modeling. Our findings suggest that applying model patterns can increase model coverage, but increases complexity, and may increase modeling effort depending on the experience of the modeler. Our conclusions indicate situations where pattern application to i* models may be beneficial.
Strohmaier M., Lux M., Granitzer Michael, Scheir Peter, Liaskos S., Yu E.
2007
Lindstaedt Stefanie , Farmer J., Hrastnik J., Rollett H., Strohmaier M.
2003
Personalisierbare Portale als Fenster zu Unternehmensgedachtnissen finden ¨in der Praxis immer haufiger Anwendung. Bei dem Design dieser Portale stellt sich die ¨Frage nach der Strukturierung der Informationen: auf der einen Seite soll der tagliche ¨Arbeitsprozess unterstutzt werden, auf der anderen Seite sollen aber auch Informa- ¨tionen zuganglich gemacht werden, die den Prozess in einen gr ¨ oßeren Kontext set- ¨zen. Unsere Erfahrungen bei der Portalentwicklungen haben gezeigt, dass zwei unterschiedlicheStrategien Anwendung finden: Prozessfokus und Wissensfokus. Die Wahlder individuellen Strategie hangt einerseits von den Zielen ab, die das Portal erf ¨ ullen ¨soll. Andererseits hangen sie aber auch von der Ausgangssituation im anwendenden ¨Unternehmen ab. Dieser Beitrag stellt die beiden Designstrategien vor und identifiziertRahmenbedingungen, die bei der Wahl der Stategie helfen konnen.
Strohmaier M.
2003
Strohmaier M.
2003
Lindstaedt Stefanie , Strohmaier M., Rollett Herwig, Hrastnik Janez, Bruhnsen Karin, Droschl Georg, Gerold Markus
2002
One of the first question each knowledge management project facesis: Which concrete activities are referred to under the name of knowledgemanagement and how do they relate to each other? To help answer this questionand to provide guidance when introducing knowledge management we havedeveloped KMap. KMap is an environment which supports a practitioner in theinteractive exploration of a map of knowledge management activities. Theinteraction helps trigger interesting questions crucial to the exploration of thesolution space and makes hidden argumentation lines visible. KMap is not anew theory of knowledge management but a pragmatic “object to think with”and is currently in use in two case studies.
Lindstaedt Stefanie , Strohmaier M.
2002