update summary as defined for the DUC2007 new task aims to capture evolving information of a single topic over time. It delivers focused information to a user who has already read a set of older documents covering the same topic. This paper presents a novel manifold-ranking frame based on iterative feedback mechanism to this summary task. The topic set is extended by using the summarization of ...

MOTIVATION Protein remote homology detection is one of the fundamental problems in computational biology, aiming to find protein sequences in a database of known structures that are evolutionarily related to a given query protein. Some computational methods treat this problem as a ranking problem and achieve the state-of-the-art performance, such as PSI-BLAST, HHblits and ProtEmbed. This raises...

The splab team participated in the Chinese subtask of the NTCIR-12 on Short Text Conversation Task. This task assumes that the existing comments in a post-comment repository can be reused as suitable responses to a new short text. Our task is to return 10 most appropriate comments to such a short text. In our system, we attempt to employ advanced IR methods and the recent deep learning techniqu...

due to increasing importance of desertification challenges and its consequences the necessity of sustainabledevelopment achievement in arid and semi-arid regions is essential in order to avoid limited sources asting, increase the efficiency of controlling, reclamation and restoration projects of natural areas. based on the iterature review, it has been recognized that combating desertification ...

The authors address the problem of unsupervised ensemble ranking. Traditional approaches either combinemultiple ranking criteria into a unified representation to obtain an overall ranking score or to utilize certain rank fusion or aggregation techniques to combine the ranking results. Beyond the aforementioned “combine-thenrank” and “rank-then-combine” approaches, the authors propose a novel “r...

This article investigates new score and accuracy functions for ranking interval-valued intuitionistic fuzzy numbers (IVIFNs). The novelty of these functions is that they allow the comparison of IVIFNs by taking into account of the decision makers’ attitudinal character. The new attitudinal expected score and accuracy functions extend Xu and Chen’s score and accuracy degree functions, and verify...

Extractive summarization of text documents usually consists of ranking the document sentences and extracting the top-ranked sentences subject to the summary length constraints. In this paper, we explore the contribution of various supervised learning algorithms to the sentence ranking task. For this purpose, we introduce a novel sentence ranking methodology based on the similarity score between...

In the design of human-computer ranking systems for the adaptive display of information, designers often define a domain-specific scoring function which maps items such as people or information search results to numeric scores. Classic ranking systems typically display these items in a linear fashion, sorted by score. There are shortcomings to this approach: such ranking systems do not provide ...

Page Rank is extensively used for ranking web pages in order of relevance by mostly all search engines world-wide. There are many algorithms for page ranking such as Google Page Rank algorithm, Hyperlink-Induced Topic Search (HITS) algorithm etc. Some search engine uses link structure based page ranking algorithm while some uses content based. The page ranking algorithm reflects the popularity ...

information to the users. To make the search effective, a tool called search engine has been introduced. These engines crawl the web for the given users query and display the results to the user based on the relevance score (ranking). Different search engine employs different ranking algorithm. Many ranking algorithm is being introduced frequently by several researchers. Several metrics are ava...