University of Delaware at TREC 2015: Combining Opinion Profile Modeling with Complex Context Filtering for Contextual Suggestion

نویسندگان

  • Peilin Yang
  • Hui Fang
چکیده

In this paper we describe our effort on TREC 2015 Contextual Suggestion Track. Using opinions from online resources to model both user profile and candidate profile has been proven to be effective on previous TREC. This year we also leverage the power of building profile based on opinions. Opinions from well known commercial online resources are collected in order to build the profiles. Two kinds of opinion representations are used for the two submitted runs. Linear interpolation is leveraged to rank the candidate suggestions. Additionally, an advanced context filter which considers all possible factors such as trip type and trip duration is applied to the ranking results so that unwanted venues are removed from the final ranking list. Official results of our submitted runs show the effectiveness of the proposed method.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

York University at TREC 2013: Contextual Suggestion Track

This paper presents our participation in the Contextual Suggestion Track of TREC 2013. The goal of this track is to investigate search techniques for complex information needs that are highly dependent on context and user interests. To achieve this goal, we propose a semantic user profile modeling for personalized place recommendation. For the semantic user profile model construction, we constr...

متن کامل

University of Delaware at TREC 2014

This paper describes the work of the Information Retrieval Lab at the University of Delaware (team name “udel”) on TREC 2014 tracks. We participated in five different tracks: Contextual Suggestion, Federated Web, Microblog, Session, and Web.

متن کامل

Laval University and Lakehead University Experiments at TREC 2015 Contextual Suggestion Track

In this paper we describe our effort on TREC Contextual Suggestion Track. We present a recommendation system that built upon ElasticSearch along with a machine learning re-ranking model. We utilize real world users’ opinion as well as other information to build user profiles. With profile information, we then construct customized ElasticSearch queries to search on various fields. After that, a ...

متن کامل

PRIS at TREC 2012 Contextual Suggestion Track

The system to Contextual Suggestion Track at TREC2012 includes information crawling and preprocessing, context filtering, user modeling, similarity computing and ranking, description generating. Some third party tool kits are used, such as URLPARSE. TF-IDF (term frequency–inverse document frequency) and cosine similarity is also used for building user models and computed similarities between us...

متن کامل

Neural Endorsement Based Contextual Suggestion

This paper presents the University of Amsterdam’s participation in the TREC 2016 Contextual Suggestion Track. In this research, we have studied a personallized neural document language modeling and a neural category preference modeling for contextual suggestion using available endorsements in TREC 2016 contextual suggestion track phase 2 requests. Specifically, our main aim is to answer the que...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2015