Abstract

In this paper we report our performance at DUC 2007 summarization tasks. We participated both in the query-focused multidocument summarization main task and in a pilot update summary generation tasks. This year we used a term clustering approach to better estimate a sentence prior. We used only the sentence prior which is query independent, in the update summarization task and found that it’s performance is comparable with the top performing systems. In the main task our system ranked 1 in ROUGE-2, ROUGE-SU4 and ROUGE-BE scores as well as in pyramid scores.

Abstract

Security is one of the major concerns of modern software development, but there is a wide gap between the industry practice and the academic instruction. Security issues are usually not addressed in academic setup and those attempt to make it as part of their software engineering curriculum realize quickly that it is difficult to make learning happen in a conventional lecture based approach. We explored a case study centered non-conventional approach and found it to be instrumental in bridging this gap between the industry and the academia. We give a detailed methodology for using the case study and our experience, observations and result of the approach. Whole case exercise aims at creating software professionals who realize the importance of security and are well versed with the related concepts, skills and dispositions and thus handle security related challenges in a structured manner.

Abstract

This paper presents the experiments of Language Technologies Research Centre (LTRC) 1 as part of their participation in CLEF2 2006 ad-hoc document retrieval task. This is our first participation in the CLEF evaluation tasks and we focused on Afaan Oromo, Hindi and Telugu as query languages for retrieval from English document collection. In this paper we discuss our Hindi and Telugu to English CLIR system and the experiments at CLEF.

Abstract

The task in Document Understanding Conferences (DUC1) 2006 is to generate a fixed length, user oriented, multi document summary, which remains same as that of DUC 2005. We have used two features to score the sentences based. The sentences are picked to form the summary based on the calculated score. The first feature is a query dependent scoring of a sentence which is an improvement over the HAL feature. The second feature is based on the observation that sentence importance, which is independent of the query, needs to be captured in the current approaches. We have explored the use of web in scoring the sentences in a query independent manner. Experiments show a performance gain of 6-7% over HAL feature by the inclusion of two new features. Our summarization system was ranked 1st in all automatic evaluations with significant margin from second best system, 5th in responsiveness and 9th in linguistic quality evaluations in DUC 2006. Relatively lower performance in linguistic quality can be attributed to the stripped off sentences at the end of summary, when the summary length is exceeding 250 words.

Abstract

Today web search engines provide the easiest way to reach information on the web. In this scenario, more than 95% of Indian language content on the web is not searchable due to multiple encodings of web pages. Most of these encodings are proprietary and hence need some kind of standardization for making the content accessible via a search engine. In this paper we present a search engine called WebKhoj which is capable of searching multi-script and multi-encoded Indian language content on the web. We describe a language focused crawler and the transcoding processes involved to achieve accessibility of Indian langauge content. In the end we report some of the experiments that were conducted along with results on Indian language web content.

Abstract

The current approaches to the software engineering education fall short to fulfill the industry demand for quality software engineering. A constant need to create and imbibe more effective learning environments is growing in order to manage this demand. This paper discusses the learning disabilities possessed by both the conventional and the non-conventional approaches for teaching software engineering. We propose that case studies can be used as effective teaching mediums and a case study centric learning environment can address these learning disabilities. A case study approach can help the students to gain and retain realistic exposure to concepts of software engineering as they are applied in the real world, and the students of today can be groomed as excellent professionals who have experienced the intricacies and complexities of the real world as well as tried their hands to manage these complexities.

Abstract

Conceptual blending is an important area of research for creativity modeling. In this paper we present a creativity model that takes an existing blend and generates new blends using the nearest neighborhood replacements from a lexical ontology. For example “Artificial Intelligence” is a compounded concept comprising of “Artificiality” and “Intelligence” as two sub-concepts. After concept generation, the system comes up with “Artificial Creativity” as one of the generated concepts. This project is part of a larger ongoing project called CAPRICON whose goal is to provide with stimuli for new futuristic concepts. This tool is a creativity enhancement tool that helps users enhance their creative thinking by providing stimuli for new concepts.

Abstract

Abstract The task in Document Understanding Conferences (DUC1) 2005 is to generate fixed length, user oriented, multi document summary. Our approach to address this task is primarily motivated by the observation that metrics based on key concepts overlap give better results when compared to metrics based on n-gram and sentence overlap. In this paper, we present a sentence extraction based summarization system which scores the sentences using Relevance Based Language Modeling, Latent Semantic Indexing and number of special words. From these scored sentences, the system generates a summary of required granularity. Our summarization system was ranked 3rd, 4th, 8th and 17th in ROUGE-SU4, ROUGE-2, responsiveness and linguistic quality evaluations respectively. In post DUC analysis we found that LSI has negative effect on the systems performance, and the performance gained by 5.4% when it is implemented using language modeling and number of special words.

Abstract

There has been an increasing need to find effective ways to impart Software Engineering Education. This paper discusses the problems the different approaches, both conventional and non conventional, face and proposes a case study approach that addresses these issues. This research aims to create a teaching methodology that will assist the teachers to create an effective learning environment and help the students to gain realistic exposure to concepts of Software Engineering as they are applied in the real world. The focus of the paper is to emphasize on creating a context to learn Software Engineering through case studies that imbibe the best practices from real world experiences.

Abstract

Adoptable, high performance, large scale ontologies that can be extended to support multimedia play a crucial role in building effective content and knowledge management systems and applications. In the context of developing a unified taxonomy and ontology network (UTON), we have undertaken the task of developing a technology framework for building large scale ontologies. This paper describes the architecture of UTON and how general purpose resources such as WordNet and open directory project can be used to create large scale ontology networks and how application specific taxonomies or ontologies can be derived from these general purpose tools and resources.