Finding Relevant Answers in Software Forums

Abstract—Online software forums provide a huge amount of valuable content. Developers and users often ask questions and receive answers from such forums. The availability of a vast amount of thread discussions in forums provides ample opportunities for knowledge acquisition and summarization. For a given search query, current search engines use traditional information retrieval approach to extract webpages containin

Catching and displaying memory cues for a mobile augmented memory system

This report goes over and details the progress of the 2013 COMP477 project “Augmenting Memory: The Digital Parrot on Mobile Devices” undertaken by Jake Bellamy and supervised by Annika Hinze at the University of Waikato. The report begins with an overview on the problem with remembering events in people’s lives and details the background information on the Digital Parrot system. It also describes the previous project that preceded this one, which began to conceptualize the Digital Parrot on mobile devices. It analyses problems with the current design of the system and addresses them. The report then goes on to conduct an in depth user study with the functioning version of the software. The user study finds design flaws and incorrect functionality in the application that would not have otherwise been apparent. Finally, the report concludes with a proposed user interface concept that addresses all of the issues found in the user study and describes how the system would work. It describes the initial implementation that has begun in building this system

TEQUILA: Temporal Question Answering over Knowledge Bases

Question answering over knowledge bases (KB-QA) poses challenges in handling complex questions that need to be decomposed into sub-questions. An important case, addressed here, is that of temporal questions, where cues for temporal relations need to be discovered and handled. We present TEQUILA, an enabler method for temporal QA that can run on top of any KB-QA engine. TEQUILA has four stages. It detects if a question has temporal intent. It decomposes and rewrites the question into non-temporal sub-questions and temporal constraints. Answers to sub-questions are then retrieved from the underlying KB-QA engine. Finally, TEQUILA uses constraint reasoning on temporal intervals to compute final answers to the full question. Comparisons against state-of-the-art baselines show the viability of our method

A model for structured document retrieval : empirical investigations

Documents often display a structure, e.g., several sections, each with several subsections and so on. Taking into account the structure of a document allows the retrieval process to focus on those parts of the document that are most relevant to an information need. In previous work, we developed a model for the representation and the retrieval of structured documents. This paper reports the first experimental study of the effectiveness and applicability of the model