The classical technique for proving termination of a generic sequential computer program involves the synthesis of a ranking function for each loop of the program. Linear ranking functions are particularly interesting because many terminating loops admit one and algorithms exist to automatically synthesize it. In this paper we present two such algorithms: one based on work dated 1991 by Sohn an...

The classical technique for proving termination of a generic sequential computer program involves the synthesis of a ranking function for each loop of the program. Linear ranking functions are particularly interesting because many terminating loops admit one and algorithms exist to automatically synthesize it. In this paper we present two such algorithms: one based on work dated 1991 by Sohn an...

Using specializations of unfold and fold on a generic tree data type we derive unranking and ranking functions providing natural number encodings for various Hereditarily Finite datatypes. In this context, we interpret unranking operations as instances of a generic anamorphism and ranking operations as instances of the corresponding catamorphism. Starting with Ackerman’s Encoding from Hereditar...

Aggregate ranking tasks are those where documents are not the final ranking outcome, but instead an intermediary component. For instance, in expert search, a ranking of candidate persons with relevant expertise to a query is generated after consideration of a document ranking. Many models exist for aggregate ranking tasks, however obtaining an effective and robust setting for different aggregat...

This paper provides an overview of the NTCIR-10 INTENT-2 task (the second INTENT task), which comprises the Subtopic Mining and the Document Ranking subtasks. INTENT-2 attracted participating teams from China, France, Japan and South Korea – 12 teams for Subtopic Mining and 4 teams for Document Ranking (including an organisers’ team). The Subtopic Mining subtask received 34 English runs, 23 Chi...

We present a pilot study on an evaluation method which is able to rank translation outputs with no reference translation, given only their source sentence. The system employs a statistical classifier trained upon existing human rankings, using several features derived from analysis of both the source and the target sentences. Development experiments on one language pair showed that the method h...

We present a new approach to summary evaluation which combines two novel aspects, namely (a) content comparison between gold standard summary and system summary via factoids, a pseudo-semantic representation based on atomic information units which can be robustly marked in text, and (b) use of a gold standard consensus summary, in our case based on 50 individual summaries of one text. Even thou...

Triple stores have long provided RDF storage as well as data access using expressive, formal query languages such as SPARQL. The new end users of the Semantic Web, however, are mostly unaware of SPARQL and overwhelmingly prefer imprecise, informal keyword queries for searching over data. At the same time, the amount of data on the Semantic Web is approaching the limits of the architectures that...

User-generated content has dominated the web’s recent growth and today the so-called real-time web provides us with unprecedented access to the real-time opinions, views, and ratings of millions of users. For example, Twitter’s 200m+ users are generating in the region of 1000+ tweets per second. In this work, we propose that this data can be harnessed as a useful source of recommendation knowle...