This paper addresses comprehensive ranking systems determining an ordering of entities by aggregating quantitative data for multiple attributes. We propose a DEA-CP (Data Envelopment Analysis Compromise Programming) model for the comprehensive ranking, including preference voting (ranked voting) to rank candidates in terms of aggregate vote by rank for each candidate. Although the DEA-CP model ...

While some web search users know exactly what they are looking for, others are willing to explore other topics related to an initial interest. Often, the user’s initial interest can be uniquely linked to an entity in a knowledge base, and in this case it is natural to recommend the explicitly linked entities for further exploration. In real world knowledge bases, however, the number of linked e...

This paper proposes an Entity Linking system that applies a topic modeling ranking. We apply a novel approach in order to provide new relevant elements to the model. These elements are keyphrases related to the queries and gathered from a huge Wikipedia-based knowledge resource.

With the growing popularity of social networking services, real time short messages, such as Facebook news feeds and Twitter tweets, are becoming increasingly important information sources. People use these services to search for and consume content about interesting topics and events. Given a keyword search for a certain topic, simply returning those messages often does not give a comprehensiv...

The WSDM Cup 2017 Triple scoring challenge is aimed at calculating and assigning relevance scores for triples from type-like relations. Such scores are a fundamental ingredient for ranking results in entity search. In this paper, we propose a method that uses neural embedding techniques to accurately calculate an entity score for a triple based on its nearest neighbor. We strive to develop a ne...

Generalizing recent attention to retrieving entities and not just documents, we introduce two entity retrieval tasks: list completion and entity ranking. For each task, we propose and evaluate several algorithms. One of the core challenges is to overcome the very limited amount of information that serves as input—to address this challenge we explore different representations of list description...

This paper describes our system and additional experimental results in NTCIR-4 QAC Task 1. The main components of our system are question classification, passage retrieval, and named entity extraction. Passage retrieval was performed by a density-based ranking method based on importance of query terms occurred in the passage. Question classification and Named entity extraction were designed by ...

Entity search is a new application meeting either precise or vague requirements from the search engines users. Baidu Cup 2016 Challenge just provided such a chance to tackle the problem of the entity search. We achieved the first place with the average MAP scores on 4 tasks including movie, tvShow, celebrity and restaurant. In this paper, we propose a series of similarity features based on both...

This is the second time we participate in the TREC-QA track. We put emphasis on candidate passage ranking and answer matching. As to named entity tagging, we applied the latest version of GATE and did some succeeding work aiming at our goal. This paper presents our methods in detail.

We present a dataset created from the Hansard House of Commons archived debates of the UK parliament (2013-2016). The resource includes fine-grained topic annotations at the document level and is enriched with additional semantic information such as the one provided by entity links. We assess the quality and usefulness of this corpus with two benchmarks on topic classification and ranking.