We will in this paper present an evaluation of how much stemming improves precision in information retrieval for Swedish texts. To perform this, we built an information retrieval tool with optional stemming and created a tagged corpus in Swedish.

This article describes how Granska – a surface-oriented system for checking Swedish grammar – is constructed. With the use of special error detection rules, the system can detect and suggest corrections for a number of grammatical errors in Swedish texts. Specifically, we focus on how erroneously split compounds and noun phrase agreement are handled in the rules. The system combines probabilistic and rule-based methods to achieve high efficiency and robustness. This is a necessary prerequisite for a grammar checker that will be used in real time in direct interaction with users. We hope to show that the Granska system with higher efficiency can achieve the same or better results than systems that use rule-based parsing alone. 1.

This paper presents a partial extension of a tool for automatic grammar checking of Swedish text. The work was carried out within a research project aiming at designing the grammar checker to meet the needs of second-language writers. The paper discusses the construction and implementation of a new set of matching rules for the grammar checking system, written with the purpose of detecting second language learners ’ writing errors related to the use of prepositions. A minor evaluation indicated high precision for the performance of this set of rules and an Fscore of 40 per cent. The paper also discusses the conclusions drawn during the research process for the future treatment of problems with the use of prepositions. 1 A grammar checker for Swedish text GRANSKA is an automatic grammar checker developed

The information in a database is usually accessed using SQL or some other query language, but if one uses a free text retrieval system the retrieval of text based information becomes much easier and user friendly, since one can use natural languages techniques such as automatic spell checking and stemming. The free text retrieval system needs first to index the database but then it is just to search the database.

Grammar errors and context-sensitive spelling errors in texts written by second language learners are hard to detect automatically. We have used three different approaches for grammar checking: manually constructed error detection rules, statistical differences between correct and incorrect texts, and machine learning of specific error types. The three approaches have been evaluated using a corpus of second language learner Swedish. We found that the three methods detect different errors and therefore complement each other. Svensk sammanfattning Grammatikfel och kontextberoende stavfel (felstavningar som bildar riktiga ord) i texter skrivna av andraspråksinlärare är svårt att detektera automatiskt. Vi har använt tre olika angreppssätt för granskningen: manuellt konstruerade feldetekteringsregler, statistiska skillnader mellan korrekt och felaktig text, samt maskininlärning av specifika feltyper. De tre metoderna har vi utvärderat på en korpus bestående av svenska uppsatser av andraspråksinlärare. Vi fann att metoderna upptäcker olika fel och därför kompletterar varandra väl. 1

Three different ways of evaluating a Swedish grammar checker are presented and discussed in this article. The first evaluation concerns measuring the program's detection capacity on five text genres. The measures (precision and recall) are often used in evaluating grammar checkers. However, in order to test and improve the usability of grammar checking software, they need to be complemented with user-oriented methods. Consequently, the second and the third evaluations presented in the article both involve users. The second evaluation focuses on user reactions to grammar error presentations, especially with regard to false alarms and erroneous error identification. The third and last evaluation focuses on problems in supporting users ' cognitive revision processes. It also examines user motives behind choosing to correct or not to correct problems highlighted by the program. Advantages and disadvantages of the different evaluation methods are discussed. 1.

Abstract. We investigated the effects of processing Swedish compounds for phrase-based SMT between Swedish and English. Compounds were split in a pre-processing step using an unsupervised empirical method. After translation into Swedish, compounds were merged, using a novel merging algorithm. We investigated two ways of handling compound parts, by marking them as compound parts or by normalizing them to a canonical form. We found that compound splitting did improve translation into Swedish, according to automatic metrics. For translation into English the results were not consistent across automatic metrics. However, error analysis of compound translation showed a small improvement in the systems that used splitting. The number of untranslated words in the English output was reduced by 50%.

Search engines constitute a key to finding specific information on the fast growing World Wide Web. Users query a search engine by using natural language to extract documents that refer to the desired subject. Sometimes no information is found because they make spelling and typing mistakes while entering their queries. Earlier reports suggest that 10-12 percent of all questions to a search engine are misspelled. The issue is how much does the use of a query spellchecker affect the performance of a search engine? This Master’s thesis presents an evaluation of how much a query spellchecker improves precision and recall in information retrieval for Swedish texts. Evaluation results indicate that spellchecking improved both precision and recall with 4 respectively 11.5 percent. Evaluering av ett stavningsstöd till en sökmotor Sammanfattning Sökmotorer är en nyckel till att kunna hitta specifik information i det snabbt växande Internet. Användaren brukar använda naturligt språk på en sökmotor för att kunna hitta den informationen han eller hon är in-tresserad av. Ibland misslyckas sökningen därför att användaren råkar stava eller skriva fel. Tidigare studier visar att 10-12 procent av alla frågor som ställs till en sökmotor är felstavade. Frågan är hur påverkar stavningsstödet resultaten av sökningen? Detta examensarbete utvärderar hur mycket en stavningskontroll kan förbättra precision och täckning vid informationssökning på svenska. Resultaten visar att stavningskontrollen förbättrade både precisionen och täckningen med 4 respektive 11.5 procent.

Turkish language is an agglutinative language. It is possible to produce a very high number of words from the same root with suffixes [1]. Language modeling for agglutinative languages needs to be different than modeling of languages like English. Such languages also have inflections but not as many as an agglutinative language. Techniques which can be used for modeling agglutinative languages are presented in this work.

This paper focuses on the transformation of grammar checking technology into a learning environment for second language writing. Our starting point is a grammar checker for Swedish, called Granska. Two studies have been conducted aimed at exploring the use of computer support for writing in the context of second language learning. In the first study, we developed a methodology to study naturalistic writing, and the impact of the grammar checker on the writer’s text. In the second study, we were interested in how the methodology developed earlier would work in an educational setting. The problems with false alarms and limited recall are definitely a sensitive issue in the context of second language learners and educational settings. Both learners and teachers are concerned about the false alarms, and without perfectly working text analyzers, new strategies for dealing with these problems have to be further explored and developed together with learners and teachers. 1