Authors:
(1) Clemencia Siro, University of Amsterdam, Amsterdam, Netherlands;
(2) Mohammad Aliannejadi, University of Amsterdam, Amsterdam, Netherlands;
(3) Maarten de Rijke, University of Amsterdam, Amsterdam, Netherlands.
Connection table
Summary and 1 Introduction
2 Methodology and 2.1 Experimental Data and Tasks
2.2 Automatic production of various dialogue contexts
2.3 Crowdsource Experiments
2.4 Experimental Conditions
2.5 Participants
3 Results and Analysis and 3.1 Data Statistics
3.2 RQ1: Effect of the Changing amount of dialogue context
3.3 RQ2: The effect of automatically created dialogue context
4 Discussions and Results
5 related work
6 CONCLUSION, LIMITATIONS AND ENDLESSED MOVEMENTS
7 Thanks and References
A. EK
3 results and analysis
We take it (Rq1) And (Rq2) An overview of the results and by providing in -depth analysis of our experiments. First we explain the basic data statistics.
3.1 Data Statistics
Compared to the examples of the C3 and C7, which is a lower number, the phase 1A shows more dialogues (C0), compared to the C3 and C7 samples, (C0).
Such ratings of dialogues were taken. This shows that in the absence of the previous context, Annotators is more prone to perceive the response of the system, because they deprive the evidence to claim otherwise. This tendency is common when user expressions lean on daily conversations, such as getting information about a previously mentioned film or asking for a suggestion similar to aspects where additional explanations are not accessing. As a result, this shows that additional explanants lead to higher rankings for the relevance of system response based on assumptions of the user’s previous questions.
Compared to C3 and C7, we observe a similar trend for use (Figure 1b), C0 has more useful dialogue. The introduction of the user’s next statement brought some uncertainty to additional explanations. It is evident in cases where the user introduces a new item not specified in the system of the system and expresses the intention of monitoring it, and the usefulness of the system has become uncertain. This uncertainty occurs, especially when additional explanters cannot access the previous context, and it makes it difficult to say whether the film has been mentioned before in the previous context.
These observations emphasize the effect of the amount of dialogue on the perception of relevance and use of additional explanations at the stage. This emphasizes the importance of taking into account contextual factors in evaluating TDSs.
Phase 2. In Stage 2, we offer findings on how different dialogue contexts affect the additional description of relevance and utility labels. When the dialogue summary is included as additional information for the return under evaluation (C0-SUM), a higher ratio of dialogues is explained in relation to the C0-LLM for relevance (52.5% against 60%, respectively); See. Figure 2a.
Unlike the observations made for the relevance level, we see that a higher percentage of dialogue in Figure 2B is not predominantly useful when additional information is given. This is 60% in C0-HEU, 47.5% in C0-LLM and 45% in C0-Toplam. Although this trend is relevant to the system responses, it is consistent with our observations in Stage 1, emphasizing that the user is not always compatible with the real information needs. We see that C0-SUM exhibits the most useful dialogue, which shows the effectiveness of providing information about relevant information to help additional explanters.
