This is the first time that our group takes part in the QA track. At TREC2005, the system we developed, Insun05QA, participated in the Main Task, which submitted answers to three types of questions: factoid questions, list questions and others questions. And we also submitted the document ranking which our answers are generated from. A new sentence similarity calculating method is used in our I...

We study the problem of list ranking in the parallel external memory (PEM) model. We observe an interesting dual nature for the hardness of the problem due to limited information exchange among the processors about the structure of the list, on the one hand, and its close relationship to the problem of permuting data, which is known to be hard for the external memory models, on the other hand. ...

There has been a recent surge of interest in studying permutation-based models for ranking from pairwise comparison data. Despite being structurally richer and more robust than parametric ranking models, permutation-based models are less well understood statistically and generally lack efficient learning algorithms. In this work, we study a prototype of permutation-based ranking models, namely,...

The ubiquity of the multimedia has raised a need for the system that can store, manage, structured the multimedia data in such a way that it can be retrieved intelligently. One of the current issues in media management or data mining research is ranking of retrieved documents. Ranking is one of the provocative problems for information retrieval systems. Given a user query comes up with the mill...

Ranking is a core problem for information retrieval since the performance of the search system is directly impacted by the accuracy of ranking results. Ranking model construction has been the focus of both the fields of information retrieval and machine learning, and learning to rank in particular has attracted much interest. Many ranking models have been proposed, for example, RankSVM is a sta...

The construction of a proof for unsatisfiability is less costly than the construction of a ranking function. We present a new approach to LTL software model checking (i.e., to statically analyze a program and verify a temporal property from the full class of LTL including general liveness properties) which aims at exploiting this fact. The idea is to select finite prefixes of a path and check t...

We present a method for model-checking of safety and liveness properties over procedural programs, by combining state and ranking abstractions with procedure summarization. Our abstraction is an augmented finitary abstraction [KP00,BPZ05], meaning that a concrete procedural program is first augmented with a well founded ranking function, and then abstracted by a finitary state abstraction. This...

In current IR approaches documents are retrieved only according to the terms specified in the query. The same answers are returned for the same query whatever the user and the search goal are. In reality, many other contextual factors strongly influence document’s relevance and they should be taken into account in IR operations. This paper proposes a method, based on language modeling, to integ...

Term weighting for document ranking and retrieval has been an important research topic in information retrieval for decades. We propose a novel term weighting method based on a hypothesis that a term’s role in accumulated retrieval sessions in the past affects its general importance regardless. It utilizes availability of past retrieval results consisting of the queries that contain a particula...

We present our approach for tackling the iUnit ranking and iUnit summarization subtasks of MobileClick2. We first conduct intent discovery based on latent topic modeling. Our iUnit ranking method exploits the discovered intents and considers the importance of an iUnit in each Web content document. We further develop our iUnit summarization model using the outcome from the iUnit ranking subtask....